Ollama
AICommonly used with
Skills using Ollama (403)
gguf-quantization
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
pydantic-ai
Build production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.
ollama-setup
Configure auto-configure Ollama when user needs local LLM deployment, free AI alternatives, or wants to eliminate hosted API costs. Trigger phrases: "install ollama", "local AI", "free LLM", "self-hosted AI", "replace OpenAI", "no API costs". Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
bdistill-knowledge-extraction
Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.
hugging-face-model-trainer
Train or fine-tune TRL language models on Hugging Face Jobs, including SFT, DPO, GRPO, and GGUF export.
local-llm-expert
Master local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio. Expert in quantization formats (GGUF, EXL2) and local AI privacy.
pydantic-ai
Build production-ready AI agents with PydanticAI — type-safe tool use, structured outputs, dependency injection, and multi-model support.
wordpress-plugin-development
WordPress plugin development workflow covering plugin architecture, hooks, admin interfaces, REST API, security best practices, and WordPress 7.0 features: Real-Time Collaboration, AI Connectors, Abilities API, DataViews, and PHP-only blocks.
performing-ai-driven-osint-correlation
Use AI and LLM-based reasoning to correlate findings across multiple OSINT sources—username enumeration, email lookups, social media profiles, domain records, breach databases, and dark-web mentions—into unified intelligence profiles with confidence scoring and link analysis.
open-notebook
Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker podcasts from research, chatting with documents using context-aware AI, searching across materials with full-text and vector search, or running custom content transformations. Supports 16+ AI providers including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral with complete data privacy through self-hosting.
perfup
Autonomous performance optimization: research, PoC, benchmark, implement, review, PR
gguf-quantization
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
open-notebook
Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker podcasts from research, chatting with documents using context-aware AI, searching across materials with full-text and vector search, or running custom content transformations. Supports 16+ AI providers including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral with complete data privacy through self-hosting.
awt-e2e-testing
AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g
gguf-quantization
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
openhands
Delegate coding to OpenHands CLI (model-agnostic, LiteLLM).
pinggy-tunnel
Zero-install localhost tunnels over SSH via Pinggy.
omni-inference
The core OpenAI-compatible inference endpoints: chat completions, embeddings, images, audio (TTS/STT), moderations, rerank, and the Responses API. The primary integration surface for AI agents.
technology-selection
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).
add-ollama-provider
Route a NanoClaw agent group to a local Ollama model instead of the Anthropic API. Ollama speaks the Anthropic API natively (v1/messages), so no provider code changes are needed — just env var overrides and a model setting. Use when the user wants to run their agent locally, cut API costs, or experiment with open-weight models. See docs/ollama.md for background.
add-ollama-tool
Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
customize
Add new capabilities or modify NanoClaw behavior. Use when user wants to add channels (Telegram, Slack, email input), change triggers, add integrations, modify the router, or make any other customizations. This is an interactive skill that asks questions to understand what the user wants.
add-ollama-tool
Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
langchain4j-spring-boot-integration
Provides integration patterns for LangChain4j with Spring Boot. Configures AI model beans, sets up chat memory with Spring context, integrates RAG pipelines with Spring Data, and handles auto-configuration, dependency injection, and Spring ecosystem integration. Use when embedding LangChain4j into Spring Boot applications, building Java LLM applications with @Bean configuration, or setting up Spring AI patterns.
langchain4j-testing-strategies
Provides unit test, integration test, and mock AI patterns for LangChain4j applications. Creates mock LLM responses, tests retrieval chains, validates RAG workflows, and implements Testcontainers-based integration tests for Java AI services. Use when unit testing AI services, integration testing LangChain4j components, mocking AI models, or testing LLM-based Java applications.
cherry-assistant-guide
Cherry Studio 产品知识库、源码路径索引、故障排查和页面导航。当用户询问 Cherry Studio 的功能、配置、报错、使用方法时触发。也适用于用户提到 provider、模型、知识库、Agent、MCP、OpenClaw、PDF、快捷短语等关键词的场景。
gemma4-local-deploy
在本机 Mac 或 Apple Silicon 上部署 Gemma 4 12B。本地安装/升级 llama.cpp，下载 GGUF 量化模型，用 llama-server 暴露 OpenAI-compatible API，或用 Ollama 暴露本地模型服务；按用户需求在默认 Q4_K_M、64K/128K 长上下文、QAT Q4_0 @ 256K、左右对比演示之间选择，配置 tmux 后台运行，验证健康检查、问答接口、资源占用和常见故障。当用户说部署 Gemma 4、Gemma 4 12B、本地大模型、长上下文、QAT、量化、llama-server、Ollama、GGUF、Mac 本地模型服务时使用。
google-calendar-tool
Google Calendar integration tool for listing and creating events via OAuth2 Calendar API access. Use when: checking upcoming events, creating appointments, or updating your schedule.
local-llm-tool
Local LLM execution tool for text generation and chat through Ollama or vLLM endpoints. Use when: running on-prem inference, calling a local GPU model, or summarizing with a self-hosted LLM.
Use whenever the user works with PDF files — reading/extracting text from PDFs (lecture notes, textbook chapters, HW problems, HW solutions, hand-written answers), converting PDFs to markdown for downstream analysis, merging/splitting PDFs, or creating PDFs. For scanned or hand-written PDFs, OCR is required (pytesseract + pdf2image). Based on Anthropic's official PDF skill (github.com/anthropics/skills/tree/main/skills/pdf).
ide-api-deprecation-tracker
Find all @deprecated APIs in the workspace, count their callers, and extract migration guidance. Produces a prioritized report sorted by call count so you know which deprecations to tackle first.
ide-dead-code-hunter
Find unused exports, dead functions, and unreachable code across the workspace using LSP analysis. Cross-verifies detectUnusedCode with findReferences to eliminate false positives. Use to clean up technical debt or before a major refactor.
ide-debug
Full debug workflow using IDE bridge tools. Runs tests to find failures, sets conditional breakpoints, evaluates expressions in the debugger, identifies root causes, applies fixes, and verifies. Use when debugging test failures or runtime issues.
ide-explore
Deep codebase exploration using IDE bridge LSP tools. Maps architecture, traces call chains, discovers entry points, and builds a mental model of unfamiliar code. Use when onboarding to a new codebase or understanding a module.
ide-monitor
Continuous IDE monitoring using bridge tools. Checks diagnostics, test results, or terminal output. Designed for use with /loop for recurring checks.
ide-quality
Multi-language code quality sweep using IDE bridge tools. Runs diagnostics across all languages, auto-fixes lint errors, organizes imports, formats code, runs tests, and optionally commits the cleanup.
ide-refactor
Safe refactoring with snapshot rollback. Creates a checkpoint, performs the refactoring using LSP rename and code actions, runs tests, and rolls back automatically if anything breaks.
ide-review
Deep PR review using IDE bridge LSP and GitHub tools. Analyzes diffs with code intelligence — follows definitions, checks references, inspects types, runs diagnostics, and posts structured review comments.
ide-type-mismatch-fix
Diagnose and fix TypeScript/language type errors using LSP diagnostics, hover, and code actions. For each type error, fetches the expected vs actual types, surfaces quickfix suggestions, and optionally applies them. Use when getDiagnostics shows type errors you want to resolve quickly.
alt-import
Parse an Exam Radar (OPTIMETA Alt plugin) export and fold its lecture-emphasis exam-probability signal into the PAIDEIA course index — write course-index/radar.md, annotate course-index/coverage.md with a lecture-emphasis column and divergence flags, and seed a gold-zone weakmap. Invoked by /paideia:alt. The export form is fixed (exam-radar:v1 marker).
answer-processing
Use whenever the user uploads a hand-written or scanned answer PDF to be graded against a reference solution. Converts answer PDFs in `answers/*.pdf` to markdown in `answers/converted/*.md` using the pdf skill (OCR as needed), then performs strategy-based grading against `converted/solutions/*.md` or `quizzes/*_answers.md`. Invoked by `/grade`.
course-builder
Use whenever the user wants to ingest a new course's materials (lecture notes, textbook chapters, HW problems, HW solutions) and build the course-specific knowledge base — patterns.md (recurring solution techniques), coverage.md (HW-to-section map with blind spots), and summary.md (topic tree). Invoked by `/ingest` and `/analyze` slash commands. Designed to be domain-general across math and physics courses (calculus, linear algebra, real/complex analysis, classical mechanics, E&M, thermodynamics, quantum, etc.).
exam-drill
Use when the user wants exam-focused drilling from the course's analyzed material. Generates twin variants of known problems (`/twin`), runs strategy-level blind drills on known problems (`/blind`), creates integration problems chaining multiple patterns (`/chain`), surfaces pattern cards (`/pattern`), and shows coverage/blind-spot maps (`/hwmap`). Reads from `course-index/patterns.md`, `course-index/coverage.md`, and `converted/solutions/*.md`. Works for any math/physics course that has been ingested and analyzed.
vision-ocr
Use whenever a hand-written or scanned answer PDF needs transcription to markdown for /grade. Three tiers — Claude native vision (default, no extra install), local Qwen3-VL 8B via ollama (opt-in privacy mode), pytesseract fallback. The engine is selected via `OCR_ENGINE` in `.course-meta` (written by /paideia:init-course) and can be overridden per-call with `/paideia:grade --ocr=<engine>`.
synalinks
Build neuro-symbolic LLM applications with Synalinks framework. Use when working with DataModel, Program, Generator, Module, training LLM pipelines, in-context learning, structured output, JSON operators, Branch/Decision control flow, FunctionCallingAgent, RAG/KAG, or Keras-like LLM workflows.
edge-router
Route AI agent compute tasks to the cheapest viable backend. Supports local inference (Ollama), cloud GPU (Vast.ai), and quantum hardware (Wukong 72Q). Use when an agent needs to decide where to run a task, optimize compute costs, check backend availability, or execute workloads across edge/cloud/quantum infrastructure.
game-dev-agent
AI agent that assists with Unity game development — sprite generation, code scaffolding, balance tuning, audio generation, in-game AI Director. Built to demonstrate AI agent engineer + game developer T-shape skill profile.
game-prototype
Unity-based mini colony-sim-style game prototype, built using game-dev-agent. Portfolio piece demonstrating AI agent + game dev T-shape skill.
game-prototype-2048
2048-lite. 4x4 grid slide puzzle. WASD/Arrow keys to slide tiles, same-number tiles merge into 2x. Built as the FOURTH framework-test in 3 minutes 46 seconds, confirming the compounding speedup hypothesis.
game-prototype-suika
Suika Game-lite 2D physics merge prototype. Built end-to-end via game-dev-agent CLI as the empirical validation of the multi-agent framework's "faster on the next prototype" claim.
game-prototype-vs-lite
Vampire-Survivors-lite. WASD survivor with auto-aim, escalating-rate enemy waves, projectile damage, XP gem pickup. Built as the THIRD framework-test, validating the "each new prototype is faster than the last" hypothesis.
goal-lock
A discipline helper for autonomous and long sessions — given the active goal in `docs/goal.md`, list the unchecked deliverable subgoals (the actual `- [ ]` items), report how many remain, and let the operator (or an autonomous worker) decide whether the next iteration should keep advancing the goal or whether the goal's `Done when` criteria are already satisfied. Does *not* alter the agent loop or override the harness — this is a transparency / discipline tool, not a runtime hook.
music-video
Generate a 60-second 9:16 vertical music video (YouTube Shorts / TikTok / Reels format) from an operator-supplied music file plus mood keywords. Use when the user provides an audio file (mp3 / wav / m4a / aac) and wants a short-form vertical video with beat-aligned cuts, mood-matched Pexels B-roll, and optional vintage post-shaders (pond ripple / breathing zoom / halation / combo). Music is the primary audio — no narration, no captions.
gliderecord-patterns
This skill should be used when the user asks to "query records", "GlideRecord", "database query", "get records", "update records", "insert record", "delete record", or any ServiceNow database operations.
apple-notes
Manage Apple Notes via the `memo` CLI on macOS (create, view, edit, delete, search, move, and export notes). Use when a user asks to add a note, list notes, search notes, or manage note folders.
apple-reminders
Manage Apple Reminders via the `remindctl` CLI on macOS (list, add, edit, complete, delete). Supports lists, date filters, and JSON/plain output.
blue-team
Defensive security — reads red-team findings and systematically patches every vulnerability. Hardens code, adds input validation, fixes permissions, and verifies each fix. Works from the latest red-team report.
handover
Generate a session handover note at the end of a work session. Saves to sessions/, updates project status, commits and pushes. Auto-invoked after long sessions (50+ turns).
instinct-status
Shows learned instincts from dqiii8.db, grouped by project and confidence. Internal diagnostic tool — not for user invocation.
intl-reports
Genera y entrega informes de internacionalización (Diagnóstico + Plan) para pymes españolas. Batch pipeline via Orchestrator v4 (core.cli) desde tmux externo. NUNCA empresa-a-empresa con Agent Haiku manual.
prompt-optimize
Analyze and optimize a prompt for the DQIII8 ecosystem. Classifies prompt type (LLM routing, image gen, TTS, agent instruction, Telegram), scores 5 dimensions, produces optimized version.
red-team
Adversarial security testing — attempts to break the codebase using real hacker techniques. Tests OWASP Top 10, prompt injection, MCP poisoning, dependency attacks, auth bypass, and vibe-coding-specific patterns. Generates exploit report. NEVER auto-invoked — user must explicitly request.
security-cycle
Run iterative red-team/blue-team cycles until the codebase is hardened. Each cycle runs /red-team, then /blue-team, then /red-team again to verify fixes hold. Stops when red-team finds 0 CRITICAL and 0 HIGH findings.
speckit
Spec-Driven Development (SDD) con github/spec-kit. Úsalo para arrancar cualquier feature no trivial en un proyecto nuevo o existente. Cubre instalación, ciclo completo SDD y restricciones críticas del entorno dqiii8.
svsi
Pre-revisión semántica de informes de internacionalización antes de subir al Drive compartido. Detecta inconsistencias entre cuestionario, diagnóstico y plan. Propone correcciones focales (surgical_edit) en sesión o genera handoff para tmux (regen_section). Trigger: "revisa el informe de X", "pre-review X", "checkea X antes de Drive", "/svsi-review X".
transcript-learn
Extract knowledge from video transcripts (YouTube, courses, seminars, podcasts) and convert to DQ knowledge chunks, skills, or agent definitions. Accepts YouTube URLs or .txt transcript files. ONLY invoked explicitly by user — never auto-invoked.
llama-cpp
Secondary local LLM inference engine via llama.cpp. This skill should be used when running GGUF models directly, loading LoRA adapters for Kothar, benchmarking inference speed, or serving models via llama-server. Includes dedicated Qwen 3.5 serve scripts (9B dense with F16 option, 35B MoE) with asymmetric KV cache and thinking mode. Complements Ollama (which remains primary for RLAMA and general use).
rlama
Local RAG system management with RLAMA. Create semantic knowledge bases from local documents (PDF, MD, code, etc.), query them using natural language, and manage document lifecycles. This skill should be used when building local knowledge bases, searching personal documents, or performing document Q&A. Runs 100% locally with Ollama - no cloud, no data leaving your machine.
ide-coverage
Test coverage heatmap from lcov or JSON coverage data. Finds coverage reports, parses line coverage per file, and renders a color-coded file-tree heatmap as HTML. Opens in the system browser.
ide-deps
Dependency graph for a file or symbol. Calls getCallHierarchy and findReferences, builds a directed graph, and renders an interactive HTML force-directed graph. Opens in the system browser.
ide-diagnostics-board
Diagnostic dashboard across the workspace. Calls getDiagnostics, groups results by severity and file, and renders a sortable color-coded HTML table. Opens in the system browser.
unblind
Routes images to Mimo/OpenAI vision API for text-only models. Use this skill when the user sends an image, asks "what's in this picture", says "analyze this screenshot", requests "OCR" or "extract text", reviews UI designs, reads charts, or uses Chinese triggers like 识别图片/看图. Self-healing setup on first run. Does NOT handle video, audio, or PDFs.
laravel-ai-sdk
Use when integrating AI agents, tool calling, embeddings, structured output, or streaming in Laravel 13 via the `laravel/ai` package. Covers 14+ providers (OpenAI, Anthropic, Gemini, Azure, Groq, DeepSeek, Ollama, Mistral, xAI, Cohere, ElevenLabs, Jina, VoyageAI, OpenRouter).
autonomous-loops
Create and manage your own autonomous loops -- recurring background jobs that run a prompt on a schedule (a daily briefing, a periodic check). Use this when you decide some work should happen on its own on a cadence, not just when asked. The user can always audit, disable, or delete loops you create.
calibrate
Interactive calibration session to teach the clone how you think, decide, and prioritize. Run /calibrate to start a session, /calibrate status to see coverage, or /calibrate <domain> to focus on a specific area (e.g., /calibrate prioritization). Use when you want to improve clone fidelity, teach it your values, or help it understand your decision-making style.
digital-marketing
Comprehensive digital marketing: Google Ads, Analytics, SEO, campaign management, and performance analysis
discord
Interact with Discord — send messages, embeds, react, manage threads, pins, search, and look up members. Use when the user asks to send a Discord message, react, read channels, create threads, or manage Discord content.
dna
Export or import your personality DNA -- a compact ~2000-token document that captures your core identity, decision patterns, values, and style. Use /dna export to save, /dna import to restore, or /dna show to preview.
gws-drive
Google Drive: Manage files, folders, and shared drives.
gws-shared
gws CLI: Shared patterns for authentication, global flags, and output formatting.
image-generation
Generate images from text prompts using Google's Gemini model. Creates photorealistic images, illustrations, concept art, and more via the generate_image tool.
reflect
Self-assessment where the clone articulates its understanding of the user and asks for corrections. Run /reflect to start a reflection session, /reflect predictions to see scenario-specific predictions, or /reflect gaps to identify blind spots.
run-evals
Run the Nomos eval suite -- recall@5, per-user isolation, and the end-to-end agent eval with the Opus-4.8 DB-content audit + the spec-driven feature-manifest audit. Use /run-evals when asked to run the evals, verify the memory system, check tenant isolation, or audit that features are actually wired and their DB effects land.
slack
Interact with Slack workspaces — send messages, react, pin/unpin, read history, manage threads, search, upload files, and look up members. Use when the user asks to send a Slack message, react to something, read a channel, or manage Slack content.
telegram
Interact with Telegram — send messages, photos, documents, locations, edit and delete messages, get chat and member info. Use when the user asks to send a Telegram message, edit content, send media, or manage Telegram chats.
twin-test
GAN-style identity verification -- tests clone fidelity by comparing clone responses against real user messages. Run /twin-test to start a blind taste test, or /twin-test score to see your fidelity score over time.
video-generation
Generate videos from text prompts using Google's Veo model. Creates short video clips with cinematic quality via the generate_video tool.
Send WhatsApp messages programmatically via the Baileys library (WhatsApp Web multi-device protocol). Use when the user asks to send a WhatsApp message or interact with WhatsApp.
gemini-best-practices
Review and fix Gemini API usage against Google's official best practices. Use when modifying src/core/gemini.ts, adding new API calls, or auditing Gemini integration quality.
terradev-gpu-cloud
Cross-cloud GPU provisioning, K8s cluster creation, and inference overflow. Get real-time pricing across 11+ cloud providers, provision the cheapest GPUs in seconds, spin up production K8s clusters, and burst to cloud when your local GPU maxes out. BYOAPI — your keys never leave your machine.
orchardcore-ai-chat
Skill for configuring AI Chat in Orchard Core using the CrestApps AI Chat module. Covers chat profiles, admin chat UI, frontend chat widgets, provider connections, and the AI Agent module for task automation. Use this skill when requests mention Orchard Core AI Chat, Configure AI Chat, Available AI Completion Providers, Enabling AI Chat Features, Setting Up a Provider Connection via Recipe, Creating a Chat Profile via Recipe, or closely related Orchard Core implementation, setup, extension, or troubleshooting work. Strong matches include work with CrestApps.OrchardCore.AI.Chat, CrestApps.OrchardCore.AI.Agent, CrestApps.OrchardCore.OpenAI, CrestApps.OrchardCore.AzureAIInference, CrestApps.OrchardCore.Ollama. It also helps with ai chat examples, Setting Up a Provider Connection via Recipe, Creating a Chat Profile via Recipe, Making a Chat Profile Visible on the Admin Menu, plus the code patterns, admin flows, recipe steps, and referenced examples captured in this skill.
null-epoch
Play The Null Epoch, a persistent AI agent MMO. Use when the user wants to connect an agent to Null Epoch, check game state, submit actions, play the game, or interact with the Null Epoch API. Handles authentication, state polling, action submission, and survival strategy for the Sundered Grid. Do NOT use for general coding tasks unrelated to Null Epoch.
ai-tools
Reference for all AI tools available in DBX Studio's AI chat system. Use when adding, modifying, or debugging AI tool definitions, tool execution, or provider integrations.
genkit
Build production-ready AI workflows using Firebase Genkit. Use when creating flows, tool-calling agents, RAG pipelines, multi-agent systems, or deploying AI to Firebase/Cloud Run. Supports TypeScript, Go, and Python with Gemini, OpenAI, Anthropic, Ollama, and Vertex AI plugins.
claude-api
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST
gws-calendar
Google Calendar: Manage calendars and events.
gws-gmail
Gmail: Send, read, and manage email.
audit
Run complete system health audit of DQIII8 — checks DB integrity, agent performance, pipeline connections, error log, and services. Produces a scored Markdown report.
checkpoint
Save and verify session state using git commits and a checkpoints log. Use before risky multi-file changes or after completing a significant implementation block.
gemini-review
Launch an efficiency audit on modified Python files using Aider + Gemini 2.0 Flash. Analyzes bugs, efficiency, readability, and security. Saves report to database/audit_reports/.
mobilize
Multi-agent coordination protocol for tasks spanning 3+ distinct domains. Decomposes goal into sub-tasks, spawns specialized agents in isolated worktrees, aggregates results.
skill-create
Analyzes DQIII8 git history to extract patterns and generate SKILL.md files in skills-registry/custom/
test-team
Agent team coordination test — research-analyst gathers Kelly Criterion info, python-specialist implements it. Validates sequential agent coordination via tasks/results/ handoff.
weekly-review
Generate weekly dashboard update — reads sessions from last 7 days, queries metrics from dqiii8.db, regenerates 00_DASHBOARD.md, commits and pushes.
open-forge
Self-host any open-source app on the user's own infrastructure (cloud VM, VPS, Raspberry Pi, localhost, k8s, PaaS). Walks the user through provisioning, DNS, TLS, SMTP, and hardening in phased + resumable workflows. 2216+ verified recipes plus live-derived fallback for the long tail. Agent-mode rules apply (no chat-paste credentials, no group-channel deploys).
chatcrystal-debug-recall
Recall ChatCrystal memories for debugging tasks involving failing tests, compiler errors, runtime exceptions, dependency issues, environment breakage, or performance regressions. Use when historical root causes, fixes, or pitfalls may accelerate diagnosis before proposing a fix.
chatcrystal-task-recall
Recall project-first and global-supplement ChatCrystal memories before substantive implementation, refactoring, migration, configuration, investigation, or optimization work. Use when the task is non-trivial, has repository or project context, and prior fixes, decisions, pitfalls, or reusable patterns may change the approach.
chatcrystal-task-writeback
Write reusable ChatCrystal task memories after substantive work completes. Use when implementation or debugging produced a durable fix, pitfall, pattern, or decision worth preserving, and when the environment can either persist it through `write_task_memory` or emit a structured memory candidate for later save.
add-tool
Add a new function calling tool (vault operation) for the Gemini chat. Use when adding new tools like read_note, create_note, etc.
add-workflow-node
Add a new workflow node type to the plugin. Use when implementing a new node type for the workflow engine (e.g., new command, integration, or control flow node).
linkedin-export
Parse, search, analyze, and ingest LinkedIn GDPR data exports. This skill should be used when working with LinkedIn data — searching messages, analyzing connections, exporting to Markdown, or ingesting into RLAMA for semantic search. Requires a LinkedIn GDPR data export ZIP file.
claude-api
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no p
orchestration
Skills for orchestrating tasks across multiple AI providers and execution environments. Parent skill category containing native-invoke and related delegation patterns.
local-llm
Hand off bulk transformation work to a local LLM via Ollama
configuring-brainpalace
Installation and configuration skill for BrainPalace document search system. Use when asked to "install BrainPalace", "setup BrainPalace", "configure BrainPalace", "setting up document search", "installing brainpalace packages", "configuring API keys", "initializing project for search", "troubleshooting BrainPalace", "pip install brainpalace", "BrainPalace not working", "BrainPalace setup error", "configure embeddings provider", "setup ollama for BrainPalace", or "BrainPalace environment variables". Covers package installation, provider configuration, project initialization, and server management.
using-brainpalace
Expert BrainPalace skill for document search with BM25 keyword, semantic vector, hybrid, graph, and multi retrieval modes. Use when asked to "search documentation", "query domain", "find in docs", "bm25 search", "hybrid search", "semantic search", "graph search", "multi search", "find dependencies", "code relationships", "searching knowledge base", "querying indexed documents", "finding code references", "exploring codebase", "what calls this function", "find imports", "trace dependencies", "brain search", "brain query", "knowledge base search", "cache management", "clear embedding cache", "cache hit rate", or "cache status". Supports multi-instance architecture with automatic server discovery. GraphRAG mode enables relationship-aware queries for code dependencies and entity connections. Pluggable providers for embeddings (OpenAI, Cohere, Ollama) and summarization (Anthropic, OpenAI, Gemini, Grok, Ollama). Supports multiple runtimes (Claude Code, OpenCode, Gemini CLI) with shared .brainpalace/ data directory.
codex-cli
Run OpenAI Codex CLI for coding tasks and second-opinion audits. Use when a user asks to run/ask/use Codex, says "codex prompt", or wants Claude to delegate a logic/code review to OpenAI models. Covers direct `codex` CLI invocation (exec, review, resume, apply, doctor, mcp), the six reasoning-effort levels (none/minimal/low/medium/high/xhigh), sandbox + dangerous flags, background execution, rate-limit safety, and when to defer to the official OpenAI Codex Claude Code plugin (`codex:rescue`) instead. Preflights with `codex doctor` to read the current default model + surface available updates; never hardcodes model/effort, letting Codex pick its own current best default unless the user explicitly names one.
conversations
How you work with the user, one ongoing relationship (one channel, no thread list) backed by your long-term memory. Use memory to stay continuous, write back what you learn, and pull a full past transcript only when you need exact wording.
doc-coauthoring
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
self-improve
Clone the Nomos repository, analyze the codebase for improvements, implement changes, and open a pull request. Use when asked to improve itself, contribute to its own codebase, fix its own bugs, add features to itself, write tests for itself, or do self-maintenance. Also triggered by phrases like 'improve yourself', 'fix your code', 'add a feature to nomos', 'update your own repo'.
aichat-all-in-one-llm-cli-with-shell-assistant-and-rag
AIChat is a comprehensive LLM command-line tool written in Rust that combines chat-REPL, shell command generation, RAG, AI tools, and multi-provider support into a single binary. It connects to 20+ LLM providers including OpenAI, Claude, Gemini, and Ollama.
extract-from-pdfs
This skill should be used when extracting structured data from scientific PDFs for systematic reviews, meta-analyses, or database creation. Use when working with collections of research papers that need to be converted into analyzable datasets with validation metrics.
model-discovery
Fetch current model names from AI providers (Anthropic, OpenAI, Gemini, Ollama), classify them into tiers (fast/default/heavy), and detect new models. Use when needing up-to-date model IDs for API calls or when other skills reference model names.
multi-agent-orchestration
Orchestrate tasks across multiple AI providers (Claude, OpenAI, Gemini, Cursor, OpenCode, Ollama). Use when delegating tasks to specialized providers, routing based on capabilities, or implementing fallback strategies.
health-probe
Health probes for both sides of the AGI stack — openclaw + arifOS MCP
subscope-setup
Reconfigure individual pieces of subscope after first-run onboarding. Use this when you want to add or change LLM provider, swap a destination (Notion / Slack / Obsidian), or rotate credentials. NOT the first-run flow. First-time users should run /subscope-onboard instead. Triggers on "/subscope-setup", "reconfigure subscope", "change subscope settings", "update subscope LLM", "rotate subscope credentials", "swap subscope destination".
ai-portable-setup
Erstellt eine portable KI-Arbeitsumgebung auf einem USB-Stick oder beliebigem Laufwerk. RAG-Pipeline mit lokalen LLM-Modellen (Ollama), Vektordatenbank (ChromaDB) und vorkonfigurierten Prompts.
model-strategy
Multi-Modell Orchestrierung und Model-Switching Strategie. Score-basierte Modellauswahl, Eskalations-Trigger, Berechtigungsmatrix und Kosten-Effizienz-Optimierung.
gws-docs
Read and write Google Docs.
gws-sheets
Google Sheets: Read and write spreadsheets.
gws-slides
Google Slides: Read and write presentations.
sales-amical
Amical platform help — open-source, local-first AI dictation app with Whisper STT, context-aware formatting, Ollama/OpenRouter LLM, MCP voice commands, and 100+ language support (MIT license). Use when setting up Amical on macOS or Windows for the first time, choosing between Whisper model sizes for accuracy vs speed, configuring Ollama for fully offline text formatting, context-aware formatting not adapting to the active application, microphone not switching or audio input issues, custom vocabulary not recognizing industry terminology, comparing Amical to Wispr Flow or Superwhisper for privacy-first dictation, or setting up voice commands with MCP integrations. Do NOT use for picking between meeting note-takers generally (use /sales-note-taker) or reviewing a single call for coaching (use /sales-call-review).
add-llama-cpp
Install and verify a local llama.cpp server for optional Deus local-generation experiments. Keeps Ollama as the required default for embeddings and judge work.
add-ollama-tool
Add Ollama MCP server so the container agent can call local models for cheaper/faster tasks like summarization, translation, or general queries.
review-logs
Review Deus system health logs, show daily reports, surface pinned issues, and rotate old log files. Uses a local Ollama model to analyze errors and warnings.
route
Route a task to the best LLM based on task type and complexity
hire
Add an agent to a workspace from the agent library. Proposes agent configuration including name, role, capabilities, adapter, and budget. Requires board approval via /approve before onboarding. Completes with identity setup and coordination prompt. Triggers on: "hire", "add agent", "onboard agent", "recruit"
aiperf
NVIDIA AIPerf — vendor-neutral generative-AI inference benchmarking (genai-perf successor). Covers `aiperf profile` with concurrency / request-rate / fixed-schedule trace replay / user-centric / multi-run confidence, 15 endpoint types (chat, completions, embeddings, rankings, responses, image-gen, video-gen, NIM, HF-TGI, template, etc.), 6 custom dataset formats (single_turn, multi_turn, mooncake_trace, bailian_trace, burst_gpt_trace, random_pool), 40+ public datasets, goodput SLOs, GPU + Prometheus telemetry, plot/analyze-trace/synthesize/service subcommands, plugin extensibility, and reasoning-token TTFT/TTFO split.
compile
Compile .agents knowledge wiki.
ai-engineer
AI/LLM Application Engineer (/ai) — builds LLM-powered product features: RAG, agentic workflows, prompt engineering, tool use, structured output, evals, and guardrails. Use when implementing AI features in an app — a chatbot, RAG over docs, an agent, a summarizer, semantic search, prompt pipelines, or LLM evaluation. Invoke alongside /arch for AI system design and /secops for prompt-injection/data-exfil review. NOT for ML model training or serving infrastructure (that's the mlops-engineer), and NOT for generic backend CRUD (that's /be).
github
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
weather
Get current weather and forecasts (no API key required).
hugging-face-model-trainer
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
local-rag-builder
本地 RAG 系统搭建技能，支持环境检测修复、嵌入模型多源下载、5种切分策略 + GuardStack + 后处理 + 插件注册、多知识库管理 + 自动分类规则、可调 Prompt、Web 可视化配置 + 极客模式 + 模板管理
council-mode
Adversarial parallel comparison — runs the SAME task across multiple model tiers and/or providers in parallel, then surfaces where each model disagrees, fails, or hallucinates. Purpose is NOT consensus: the purpose is exposing failure modes so the operator can route around them. Built on top of advisor-mode. Trigger on: "assemble the council", "convene the council", "put it to the council", "what does the council say", "council mode", "run this on all tiers", "compare model outputs", "which model failed on this", "adversarial compare", "diff the models", "run the council", "parallel dispatch", "show me the disagreements".
orchestrator-mode
Sequential chain routing — decomposes a compound task into subtasks, routes each subtask to its optimal tier (via advisor-mode underneath), runs a quality-gate check after each step, and escalates to a higher tier on gate failure. Complements council-mode (parallel comparison). Orchestrator is the "route around failure" thesis applied sequentially: keep each subtask on the cheapest tier that passes, escalate only when the gate fails. Trigger on: "orchestrator mode", "chain this", "break this into subtasks", "route each step", "escalation pipeline", "run this as a chain", "decompose and route", "quality- gated routing", "sequential tier routing", "run the orchestrator".
research-agent
Perform grounded research and produce cited briefs.
claude-api
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no p
business-growth-skills
4 business growth agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Customer success (health scoring, churn), sales engineer (RFP), revenue operations (pipeline, GTM), contract & proposal writer. Python tools (stdlib-only).
brainstorm
Send a topic to multiple LLM providers in parallel while Claude Opus performs its own independent research in parallel, then synthesize all findings. Usage /brainstorm [providers] <topic>. External providers default to antigravity,codex. Example /brainstorm antigravity,codex,ollama "review this architecture"
compare
This skill should be used when the user asks to "compare LLMs", "see how each provider answers", "side-by-side response", "what do Gemini, Codex, and Ollama think", or wants raw responses from multiple providers without synthesis. Unlike /brainstorm (which synthesizes findings) or /multi-review (which validates code reviews), /compare just shows each provider's answer side-by-side.
cross-model-review
gstack /codex 패턴 — 다중 AI 모델 합의 리뷰 (Claude + Ollama + Gemini)
agenticx-agent-builder
Guide for creating and configuring AgenticX agents with roles, goals, tools, LLM providers, and execution strategies. Use when the user wants to create agents, assign tools to agents, configure LLM backends, set up agent execution, or build multi-agent systems.
agenticx-agent-builder
Guide for creating and configuring AgenticX agents with roles, goals, tools, LLM providers, and execution strategies. Use when the user wants to create agents, assign tools to agents, configure LLM backends, set up agent execution, or build multi-agent systems.
agenticx-agent-builder
Guide for creating and configuring AgenticX agents with roles, goals, tools, LLM providers, and execution strategies. Use when the user wants to create agents, assign tools to agents, configure LLM backends, set up agent execution, or build multi-agent systems.
agent-protocol
Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.
board-deck-builder
Assembles comprehensive board and investor update decks by pulling perspectives from all C-suite roles. Use when preparing board meetings, investor updates, quarterly business reviews, or fundraising narratives. Covers structure, narrative framework, bad news delivery, and common mistakes.
board-meeting
Multi-agent board meeting protocol for strategic decisions. Runs a structured 6-phase deliberation: context loading, independent C-suite contributions (isolated, no cross-pollination), critic analysis, synthesis, founder review, and decision extraction. Use when the user invokes /cs:board, calls a board meeting, or wants structured multi-perspective executive deliberation on a strategic question.
c-level-advisor
10 C-level advisory agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. CEO, CTO, COO, CPO, CMO, CFO, CRO, CISO, CHRO, Executive Mentor. Multi-role board meetings, strategy routing, structured recommendations. For founders needing executive-level decision support.
c-level-agents
Founder-mode executive team. 8 cs-* C-suite agents (CFO, CMO, CRO, CPO, COO, CHRO, CISO, Chief of Staff) and 17 /cs:* slash commands for forcing-question office hours, multi-role boardroom deliberation, strategic sprint pipeline, and meta routing. Use when the founder needs a virtual executive team, when invoking /cs:* commands, or when orchestrating multi-role decisions.
ceo-advisor
Executive leadership guidance for strategic decision-making, organizational development, and stakeholder management. Use when planning strategy, preparing board presentations, managing investors, developing organizational culture, making executive decisions, fundraising, or when user mentions CEO, strategic planning, board meetings, investor updates, organizational leadership, or executive strategy.
cfo-advisor
Financial leadership for startups and scaling companies. Financial modeling, unit economics, fundraising strategy, cash management, and board financial packages. Use when building financial models, analyzing unit economics, planning fundraising, managing cash runway, preparing board materials, or when user mentions CFO, burn rate, runway, fundraising, unit economics, LTV, CAC, term sheets, or financial strategy.
chief-ai-officer-advisor
Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding whether to call an API or fine-tune, classifying AI use cases for regulatory risk, calculating when self-hosting pays off, sequencing AI hires, or when user mentions CAIO, AI strategy, model selection, foundation model, fine-tuning, EU AI Act, NIST AI RMF, AI governance, model risk, or AI economics. Strategic only — does not duplicate engineering AI/ML skills.
chief-customer-officer-advisor
Chief Customer Officer advisory for startups: retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy), customer segmentation strategy (differential investment across tiers + ICP fit scoring), CS team coverage model (pooled vs named CSM thresholds + ratio math), and CS team org evolution (CS vs Support vs AM distinctions). Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires. Strategic only — does not duplicate engineering/business-growth tactical skills.
chief-data-officer-advisor
Chief Data Officer advisory for startups: AI training data rights and consent provenance, data product strategy (warehouse vs lakehouse vs mesh, build-vs-buy), B2B customer-data-as-asset valuation and M&A readiness, data team org evolution. Use when deciding whether to train models on customer data, choosing data architecture, valuing data for fundraising or M&A, sequencing data hires, or when user mentions CDO, chief data officer, data strategy, data mesh, lakehouse, training data, data product, data monetization, or customer data asset. NOT a tactical data engineering skill — strategic decisions only.
chief-of-staff
C-suite orchestration layer. Routes founder questions to the right advisor role(s), triggers multi-role board meetings for complex decisions, synthesizes outputs, and tracks decisions. Every C-suite interaction starts here. Loads company context automatically.
chro-advisor
People leadership for scaling companies. Hiring strategy, compensation design, org structure, culture, and retention. Use when building hiring plans, designing comp frameworks, restructuring teams, managing performance, building culture, or when user mentions CHRO, HR, people strategy, talent, headcount, compensation, org design, retention, or performance management.
customer-success-manager
Monitors customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models for SaaS customer success. Use when analyzing customer accounts, reviewing retention metrics, scoring at-risk customers, or when the user mentions churn, customer health scores, upsell opportunities, expansion revenue, retention analysis, or customer analytics. Runs three Python CLI tools to produce deterministic health scores, churn risk tiers, and prioritized expansion recommendations across Enterprise, Mid-Market, and SMB segments.
executive-mentor
Adversarial thinking partner for founders and executives. Stress-tests plans, prepares for brutal board meetings, dissects decisions with no good options, and forces honest post-mortems. Use when you need someone to find the holes before the board does, make a decision you've been avoiding, or understand what actually went wrong.
general-counsel-advisor
General Counsel advisory for startups: contract review (MSA, SaaS, NDA, DPA, employment), IP strategy, term sheet decoding, and regulatory landscape mapping. Use when reviewing any contract or term sheet, deciding when to engage outside counsel, defining IP strategy, evaluating regulatory exposure (HIPAA, GDPR, FDA, fintech), or when user mentions general counsel, GC, legal review, contract risk, term sheet, IP assignment, or regulatory exposure. NOT a substitute for licensed counsel — surfaces questions to bring to qualified attorneys.
dare-llm-integration
Integração com LLMs (Large Language Models) em projetos DARE. Fornece abstração LLMProvider, cache em memória com TTL, rate limiting via token bucket, prompt templates versionados e validação de output via JSON Schema. Cobre antipatterns crítico de prompt injection e LLM output não validado.
dare-telemetry
Rastreamento de tokens e modelos de IA consumidos em cada etapa do Método DARE. Gera DARE/TELEMETRY.md com modelo usado, tokens estimados, tempo e tentativas (Ralph Loop) por comando — para auditoria, monitoramento de uso e otimização de custos.
adk-pr-review
Deep PR review: tree-sitter AST chunking + ollama embeddings + LanceDB hybrid (vector + BM25) retrieval + SCIP cross-file symbols + harness-LLM reranker + feature-flow tracing + accept/reject/edit triage before posting. Triggers on a GitHub or Bitbucket Cloud pull-request URL OR no arg at all — when no URL is passed, the next eligible row from `$ADK_CONFIG_HOME/pr-queue.json5` is atomically claimed (FIFO by last_checked_at, 30-min auto-expiring `taken_at` lock so two terminals review different PRs). Curate the queue via `adk pr-scan` (scans Slack threads for PR links — main message AND replies — and upserts rows). When a URL is passed and that PR is already in the queue, the row's `slack` + `supporting_docs` are merged into the review context. **Global skill** — runs from anywhere; isolates to `$ADK_DATA_HOME/skill-pr-review/<repo>_pr-<n>/` (per `shared/paths.md`); never touches the cwd. Pipeline: clone+worktree at the PR head, tree-sitter chunker → ollama embed (`nomic-embed-text` default, `bge-m3` via `--de
claude-api
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no p
telegram-chat-history-persistence
Design and implement context continuity for a Telegram → Claude gateway. Use when the bot loses cross-session context or when choosing between transcript injection, SQLite buffering, RAG, and MemPalace for chat history.
clawcache-free
Smart LLM cost tracking and caching for Python
compare
Multi-model code review. Fan out a bug or task to multiple LLMs, diff their findings, optionally debate, then dispatch subagents to fix in parallel. Use when the user types /compare or asks to compare models on a code issue.
brainstorm-all
Send a topic to ALL LLM providers (Gemini, Codex, Ollama, Antigravity) in parallel while Claude Opus performs its own independent research in parallel. Synthesizes findings from up to five participants. Shortcut for /brainstorm gemini,codex,ollama,antigravity <topic>. Requires Ollama running locally and agy installed for the Antigravity participant.
grepai-chunking
Configure code chunking in GrepAI. Use this skill to optimize how code is split for embedding.
grepai-config-reference
Complete configuration reference for GrepAI. Use this skill when you need to understand all available configuration options.
grepai-embeddings-lmstudio
Configure LM Studio as embedding provider for GrepAI. Use this skill for local embeddings with a GUI interface.
grepai-embeddings-ollama
Configure Ollama as embedding provider for GrepAI. Use this skill for local, private embedding generation.
grepai-embeddings-openai
Configure OpenAI as embedding provider for GrepAI. Use this skill for high-quality cloud embeddings.
grepai-ignore-patterns
Configure ignore patterns in GrepAI. Use this skill when excluding files and directories from indexing.
grepai-init
Initialize GrepAI in a project. Use this skill when setting up GrepAI for the first time in a codebase.
grepai-installation
Multi-platform installation guide for GrepAI. Use this skill when installing GrepAI on macOS, Linux, or Windows.
grepai-languages
Supported programming languages in GrepAI. Use this skill to understand which languages can be indexed and traced.
grepai-mcp-claude
Integrate GrepAI with Claude Code via MCP. Use this skill to enable semantic code search in Claude Code.
grepai-mcp-cursor
Integrate GrepAI with Cursor IDE via MCP. Use this skill to enable semantic code search in Cursor.
grepai-mcp-tools
Reference for all GrepAI MCP tools. Use this skill to understand available MCP tools and their parameters.
grepai-ollama-setup
Install and configure Ollama for local embeddings with GrepAI. Use this skill when setting up private, local embedding generation.
grepai-quickstart
Get started with GrepAI in 5 minutes. Use this skill for a complete walkthrough from installation to first search.
grepai-search-advanced
Advanced search options in GrepAI. Use this skill for JSON output, compact mode, and AI agent integration.
grepai-search-basics
Basic semantic code search with GrepAI. Use this skill to learn fundamental search commands and concepts.
grepai-search-boosting
Configure search result boosting in GrepAI. Use this skill to prioritize certain paths and penalize others.
grepai-search-tips
Tips and best practices for effective GrepAI searches. Use this skill to improve search result quality.
grepai-storage-gob
Configure GOB local file storage for GrepAI. Use this skill for simple, single-machine setups.
grepai-storage-postgres
Configure PostgreSQL with pgvector for GrepAI. Use this skill for team environments and large codebases.
grepai-storage-qdrant
Configure Qdrant vector database for GrepAI. Use this skill for high-performance vector search.
grepai-trace-callees
Find function callees with GrepAI trace. Use this skill to discover what functions a specific function calls.
grepai-trace-callers
Find function callers with GrepAI trace. Use this skill to discover what code calls a specific function.
grepai-trace-graph
Build complete call graphs with GrepAI trace. Use this skill for recursive dependency analysis.
grepai-troubleshooting
Troubleshooting guide for GrepAI. Use this skill to diagnose and fix common issues.
grepai-watch-daemon
Configure and manage the GrepAI watch daemon. Use this skill for real-time code indexing and file monitoring.
grepai-workspaces
Configure multi-project workspaces in GrepAI. Use this skill for monorepos and multiple related projects.
model-serving
LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming patterns.
advisor-mode
Tiered model routing — classifies incoming tasks by complexity and dispatches to the correct model tier: Tier C (Haiku, simple/high-volume), Tier B (Sonnet, mid-complexity), Tier A (Sonnet + Opus advisor, strategic/complex), Tier A+ (Opus solo, highest stakes). Uses Anthropic's native advisor_20260301 API tool for Tier A dispatch. Enforces plan-before-act discipline: Opus advises on the PLAN, executor carries out the plan. Budget control via max_uses parameter. Trigger on: "what tier is this", "classify this task", "dispatch this", "which model should handle", "advisor mode", "route this task", "run this as tier A", "check my advisor budget", "run with opus advisor", "advisor dispatch", "tier routing".
postmortem
Detect your replies to surfaces and score their 7-day outcome (upvotes, replies, banned). Closes the loop on which patterns convert vs flop. Requires Reddit OAuth identity scope (set up via docs/setup-oauth.md). Triggers on "postmortem", "/subscope:postmortem", "score my replies", "did my reddit replies work", "reddit reply outcomes", "reply post-mortem".
litopys-memory
Use whenever the conversation involves the user's projects, systems, infrastructure, people, past decisions, or recurring problems — even when memory is not explicitly mentioned. Trigger on possessives and project references ("my project", "our server", "remember when we", "last time"), named systems and services in the user's graph (check litopys://startup-context for the exact names), references to past discussions, factual claims about the user's setup, or new stable knowledge worth recording. Always consult the graph before stating facts about user-specific things; record durable knowledge using the decision tree. Skip for generic programming/library questions unrelated to the user's stack.
ai-agent-workflow
Use when designing or improving AI engineering workflows after the stack direction is already mostly known. Covers prompt pipelines, MCP integrations, tool-using agents, reusable workflow specs, evaluation loops, and workflow decomposition. Trigger this for agent architecture, prompt refinement, tool grounding, workflow design, and turning repeatable AI tasks into durable systems. If the main question is local model selection, deployment path, or LM Studio versus Ollama versus MLX, use local-ai-systems-studio instead. If the main request is to create, rewrite, benchmark, or improve a skill itself, use skill-creator instead even when the skill is AI-related.
jarvis-deep-interview
Convergent Socratic interview that turns vague requirements into a production-grade specification via 8-15 narrowing rounds with mathematical ambiguity gating. Inspired by Sorbh/interview-me, adds Contrarian/Simplifier Challenge Mode and JSONL decision log. Use when an idea exists but implementation decisions are still undefined.
jarvis-goal
Goal-driven autonomous execution with completion-condition gating and built-in irreversibility guard. Port of Anthropic /goal (Claude Code v2.1.139) that automatically pauses for explicit user approval when detecting unrecoverable operations — git push, repo visibility changes, payment, secret exposure, mass data deletion.
jarvis-plan-review
11-section rigorous design plan review covering problem framing, scope, architecture, security, observability, deployment, performance, reliability, testing, maintainability, and migration. Korean adaptation of gstack /plan-ceo-review, tuned for sole-developer + AI-pair-programming workflows. Not a rubber stamp — pushes plans toward best-in-class.
onboarding
Jarvis 초기 설치 온보딩 마법사. Discord 봇 토큰·Claude API 키 등 필수 환경변수를 단계별로 수집하고, 자동/수동 업데이트 정책을 설정하며, 전용 업데이트 알림 채널(🚀jarvis-update)을 생성합니다. 완료 시 봇이 즉시 기동됩니다.
remember
오너가 방금 말한/확정한 사실을 Jarvis 위키(`~/jarvis/runtime/wiki/`)에 즉시 주입합니다. 디스코드·Claude Code CLI·macOS 앱 어디서 호출하든 동일한 뇌에 쌓이며, source 태그로 호출 표면이 자동 구분됩니다. 오너의 명시적 "기억해" 요청이나 대화 중 확정된 사실·결정·선호를 즉시 영속시킬 때 사용합니다.
knowledge-system-bootstrap
Bootstrap a compile-first project knowledge system with repo-local wiki, raw manifests, provenance tracking, auto-update checks, and platform configs for Claude Code / Codex / Cursor / Windsurf. Use when a user wants durable project context, wiki-first rules, or to replicate this model into another repo.
agent-skill-visualizer
Claude Code 프로젝트의 에이전트와 스킬 관계를 D3.js 노드 그래프로 시각화합니다. 에이전트-스킬 의존성을 파악하고 구조를 탐색할 때 사용하세요.
board-prep
Board meeting preparation for the adversarial scenario, not the friendly one. Forces numbers-cold mastery, anticipates hard questions, builds a narrative that acknowledges weakness without losing the room. Use when preparing for a board meeting, an investor update, fundraising presentation, or any high-stakes adversarial review where every number must live in your head not just on a slide.
boardroom
/cs:boardroom <brief> — 6-phase multi-role deliberation across the C-suite with Phase 2 isolation, critic pre-screen, and synthesis. Outputs a board memo.
brief
/cs:brief <topic> — Generate a one-page strategy brief from an office-hours intake. First step in the strategic sprint pipeline.
caio-review
/cs:caio-review <plan> — Eval-demanding Chief AI Officer interrogation of any plan that involves AI: model selection, risk classification, cost economics, or AI hiring.
cco-review
/cs:cco-review <plan> — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring.
cdo-review
/cs:cdo-review <plan> — Decision-driven Chief Data Officer interrogation of any plan that touches training data, data architecture, data productization, or data team hiring.
cfo-review
/cs:cfo-review <plan> — Numerate-skeptic interrogation of any plan that touches money. Unit economics, runway, dilution, capital allocation.
challenge
Pre-mortem plan analysis. Imagine the plan failed 12 months from now and work backwards to find the weaknesses. Surfaces assumptions, dependencies, and execution risks before committing resources. Use when before significant resource commitment, before presenting to a board or investors, when feedback has been one-sidedly positive, or when there is pressure to move fast and figure it out later.
ciso-review
/cs:ciso-review <plan> — Risk-paranoid interrogation of any plan that touches data, compliance, or production access.
cmo-review
/cs:cmo-review <plan> — Narrative-first interrogation of positioning, ICP, message house, and channel mix.
cpo-review
/cs:cpo-review <plan> — JTBD-driven interrogation of product roadmap, PMF signal, and portfolio focus.
cro-review
/cs:cro-review <plan> — Pipeline-paranoid interrogation of revenue, win rate, NRR, and ramp time.
cross-eval
/cs:cross-eval <memo> — Multi-model consensus on a board memo or strategy brief. Claude + Codex + Gemini cross-review with graceful degradation.
cto-review
/cs:cto-review <plan> — Architecture and scaling interrogation. Tech debt, scaling cliffs, team scaling, build-vs-buy.
decide
/cs:decide <memo> — Log a decision to two-layer memory via decision-logger. Approved memo becomes durable; raw transcripts kept for reference.
execute
/cs:execute <decision> — Generate a 90-day execution plan with weekly milestones, DRIs, and check-in cadence from an approved decision.
founder-mode
/cs:founder-mode <question> — Auto-routes any founder question to the right C-role advisor or to /cs:boardroom for multi-role topics. The single-command entry point.
freeze
/cs:freeze <decision> <days> — Lock a strategic decision for a cooldown period to prevent impulse reversal. Mirrors gstack's safety primitives for the business layer.
gc-review
/cs:gc-review <plan> — General Counsel interrogation of contracts, IP, regulatory, term sheets, and employment-law surface.
hard-call
/em -hard-call — Framework for Decisions With No Good Options
office-hours
/cs:office-hours <topic> — YC-style 6-question founder interrogation before any advice. Forces clarity on problem, customer, distribution, defensibility, capital, and founder fit.
onboard
/cs:onboard — Founder interview that populates ~/.claude/company-context.md. The first command to run when starting with c-level-agents.
post-mortem
/cs:post-mortem <decision> — Honest retrospective on an executed decision, scored against original assumptions and dissent. Closes the strategic sprint loop.
postmortem
/em -postmortem — Honest Analysis of What Went Wrong
revenue-operations
Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization. Use when analyzing sales pipeline coverage, forecasting revenue, evaluating go-to-market performance, reviewing sales metrics, assessing pipeline analysis, tracking forecast accuracy with MAPE, calculating GTM efficiency, or measuring sales efficiency and unit economics for SaaS teams.
sales-engineer
Analyzes RFP/RFI responses for coverage gaps, builds competitive feature comparison matrices, and plans proof-of-concept (POC) engagements for pre-sales engineering. Use when responding to RFPs, bids, or proposal requests; comparing product features against competitors; planning or scoring a customer POC or sales demo; preparing a technical proposal; or performing win/loss competitor analysis. Handles tasks described as 'RFP response', 'bid response', 'proposal response', 'competitor comparison', 'feature matrix', 'POC planning', 'sales demo prep', or 'pre-sales engineering'.
stress-test
/em -stress-test — Business Assumption Stress Testing
vpe-review
/cs:vpe-review <plan> — Throughput-first VP of Engineering interrogation of any plan that touches delivery, eng hiring, team structure, or production discipline.
budget
Set up free-claude-code proxy — route Claude Code and Roo Code traffic to OpenRouter free tier, Ollama local models, NVIDIA NIM, or DeepSeek to save Anthropic credits on non-critical work
ollama-review
Get a second opinion from a local Ollama LLM on your current code changes. Analyzes staged/unstaged diffs and returns prioritized findings. No API keys needed. Use when user asks to "review with Ollama", "local code review", or "review offline".
exaaiagent
Run, debug, maintain, or extend ExaAiAgent for AI-assisted penetration testing, attack-surface mapping, repo/code security review, and multi-agent offensive-security workflows. Use when an AI agent needs onboarding instructions for operating ExaAiAgent, when a user wants to launch scans from CLI/TUI, when ExaAiAgent itself needs maintenance, or when another agent should use ExaAiAgent with any LiteLLM-supported provider (OpenAI, Anthropic, OpenRouter, Ollama, Gemini-compatible endpoints, and other LiteLLM-backed providers).
uniprot
UniProt protein database - accessions, annotations, and programmatic access
ralpharchive
Archive the current Ralph prd.json and progress.txt before starting a new feature. Use when you need to archive a completed or abandoned Ralph run. Triggers on: archive ralph, archive prd, ralph archive, clear ralph, reset ralph.
adk-cli
Python package home for the `adk` CLI subcommands. NOT a slash-invokable skill — install.py skips this directory when symlinking skills into agent skill dirs. The `adk` binary at `<repo>/bin/adk` is symlinked to `~/.local/bin/adk` at install time and dispatches to the modules under `scripts/`.
opencode-providers
Use this skill when configuring LLM providers in OpenCode, setting up API keys, connecting providers via /connect, configuring custom OpenAI-compatible providers, setting up local models (Ollama, llama.cpp, LM Studio), or troubleshooting provider authentication issues. Covers all 75+ supported providers, OpenCode Zen, OpenCode Go, provider-specific options, and environment variable configuration.
accessibility-checker
Quick A11y review - WCAG 2.1 checklist, screen reader compatibility, keyboard navigation, color contrast
ai-image-prompting
Crafts production-grade prompts for AI image generation (Midjourney, Flux, SDXL, Firefly, Imagen, ComfyUI workflows) — subject, composition, lighting, style references, negative prompts, ControlNet hints. Use when the goal is on-brand, repeatable imagery rather than a one-off lucky generation.
ai-model-selector
Quick guidance on choosing AI models (LLM/VLM/Embedding) based on task, VRAM, cost, and quality requirements
ai-prompting
Quick tips and templates for effective prompt engineering - few-shot examples, chain-of-thought patterns, constraint specification, output formatting
api-designer
Expert guidance on API design including REST vs GraphQL vs gRPC selection, endpoint patterns, authentication strategies, and versioning
architect
Design complex system architectures, evaluate tradeoffs, and make critical technical decisions requiring deep reasoning
architecture-consultant
Expert guidance on cross-domain architecture decisions, technology selection, and infrastructure design requiring deep analysis of tradeoffs and long-term implications
batch-image-pipeline
Writes batch image and video processing scripts (Pillow, ImageMagick, ffmpeg) for asset pipelines — generate size variants, format conversions, colorspace transforms, watermarks, optimization. Use when one design output needs to become 40 deliverables, or when an asset library needs cleanup.
build-vs-buy-decision
Helps a solo founder or small team decide whether to build a feature in-house, buy/integrate a SaaS, or defer it. Considers MRR stage, team capacity, vendor lock-in risk, ongoing maintenance cost, and the "default to building" indie bias. Invoked when the user asks "should we build or buy [feature]", "is it worth integrating [tool]", "should we replace [vendor] with our own implementation", or "what's the cheapest way to ship [capability]".
code-review-expert
Deep code analysis identifying subtle bugs, security issues, performance problems, and architectural concerns requiring expert-level reasoning
consulting-due-diligence
Runs structured technical due diligence on a vendor, acquisition target, or strategic partner; produces a risk-ranked report with findings, evidence, and a recommendation
consulting-incident-coordinator
Coordinates multi-channel incident response for a consulting engagement - drafts war-room updates, status-page entries, client comms, and the post-incident review; use when a client production issue is active or just resolved
consulting-portfolio-status
Turns a directory of per-client engagement files into a board-ready portfolio status report; use when preparing a weekly digest, a steering-committee briefing, or any multi-engagement roll-up
content-calendar-planner
Builds a 30/60/90-day cross-platform content calendar for a vendor across Instagram, TikTok, LinkedIn, X, YouTube Shorts, and newsletter. Takes a theme and cadence as input, produces a dated calendar with hooks, hashtags, CTAs, and a repurposing graph showing which posts feed which platforms. Use when the user says "plan content for next month/quarter", "build a content calendar", or "I need 30 days of posts".
context
Efficient context state inspection, task lifecycle management, and session tracking
database-advisor
Expert guidance on database design, schema optimization, query performance, and database technology selection
deployment-advisor
Deployment strategy guidance - platform selection, CI/CD pipeline design, environment configuration, monitoring
explore-codebase
Systematic codebase onboarding. Builds a mental model of a new or unfamiliar project by exploring structure, architecture, key data models, entry points, and auth patterns.
extract-docs
Systematically extract knowledge from scattered documentation to prevent catastrophic forgetting. Creates structured extraction reports with status tags.
fix-issue
Investigate and fix a GitHub issue or bug report. Reads the issue, reproduces it, identifies root cause, implements fix, adds regression test.
gui-test
Automated visual testing with Playwright MCP - test web apps, presentations, websites, and documents with scalable reviewer perspectives
gui-ux-expert
Quick GUI/UX/UI design consultations and recommendations
hardware-calculator
Quick VRAM/RAM calculations, hardware recommendations, feasibility checks for AI models
idempotency-keys
Designs the idempotency strategy for a state-changing operation - key derivation, storage choice, TTL, collision handling, and threading through downstream side effects. Use when adding a new endpoint with side effects, hardening an existing one, or designing a workflow that survives retries
interview
Interview the user using AskUserQuestion to discover requirements for a feature or task. Probe technical implementation, UX, edge cases, and constraints. Writes final spec to SPEC.md.
kg-research
Research using ONLY knowledge graph semantic search (no file tools, forces KG-first approach)
photoshop-scripting
Writes Adobe Photoshop automation scripts in UXP (JavaScript) or legacy ExtendScript (JSX), and GIMP scripts in Python (Script-Fu fallback). Use when a repetitive Photoshop task needs to run on dozens of files, when a custom panel/plugin is wanted, or when an Action recorder won't capture the logic needed.
react-patterns
React best practices - component patterns, state management selection, performance optimization, testing strategies
repro-audit
Audits a scientific project for reproducibility — environment pinning, seed setting, data hashing, notebook discipline, workflow orchestration, and provenance capture. Use when the user asks "is this project reproducible", "what's missing for a reviewer to rerun this", "audit my repo before submission", "why do I get different results each run", or before submitting code with a manuscript.
saas-metrics-health-check
Performs a diagnostic on a SaaS product's revenue and retention metrics from a CSV or spreadsheet of customers/subscriptions/events. Computes MRR, ARR, churn (gross/net), LTV, CAC, payback period, quick ratio, and cohort retention; flags anomalies; identifies the single highest-leverage fix. Invoked when the user asks "are my SaaS metrics healthy", "compute LTV for my data", "is my churn high", "review my MRR breakdown", or shares a billing/customer CSV.
saas-pricing-strategist
Analyses a SaaS product's pricing page (current and competitor) and produces a concrete redesign with tier structure, value metric, anchoring, annual-discount math, and a measurable rollout plan. Invoked when the user asks "is my pricing right", "review my pricing page", "compare my pricing to [competitor]", "how should I raise prices", "should I add a third tier", or shares a competitor pricing URL with intent to react.
security-reviewer
Cross-layer security analysis (frontend XSS/CSRF, backend injection, AI prompt injection, infrastructure)
slo-designer
Designs SLIs, SLOs, and multi-window multi-burn-rate alerts from a service description, then emits the Prometheus recording rules and alerting rules. Invoke when a service needs its first SLO, when an existing threshold-alert is flapping or missing real incidents, or when an SRE team is operationalising error budgets.
stats-consult
Recommends the appropriate statistical test given a data description and research question, including assumption checks, alternatives if violated, sample-size guidance, and effect-size reporting. Use when the user asks "what test should I use", "is this t-test the right choice", "how many subjects do I need", "what's the right way to analyse this dataset", or describes a dataset + hypothesis without a chosen method.
structured-output-extraction
Builds a reliable LLM-powered extraction pipeline for messy inputs (PDFs, emails, transcripts, HTML) into a strict JSON schema with validation, automated correction loop, and observability. Use when designing extraction from unstructured documents or hardening one that fails too often
task-breakdown
Break complex features into implementable tasks with estimates, dependencies, and risk assessment
terraform-plan-reviewer
Reviews Terraform/OpenTofu plan output for destructive changes, drift, IAM expansions, hardcoded values, and unsafe resource recreations before apply. Invoke when the user shares plan output, when a CI plan job posts a diff to a PR, or before any non-trivial production apply.
evolve
Evolutionary search for agent improvement using Mind Evolution. Manages multiple parallel improvement islands via git worktrees, with selection and cross-pollination. Invoke with /evolve, "evolve my agent", "run evolutionary search", "parallel improvement".
ratchet
Autonomous ratchet loop for agent improvement. Configures optimization targets, then loops: improve agent → run agent → eval → keep or revert. Uses the /recursive-improve pipeline internally with auto-approval. Invoke with /ratchet or "run the ratchet loop", "improve my agent overnight", "autonomous improvement".
recursive-improve
End-to-end agent improvement pipeline. Analyzes raw execution traces, extracts insights, manages a skillbook, gathers domain context, defines metrics, builds a rubric, creates a prioritized action plan, presents it for review, and implements approved fixes. Trigger when the user says "improve my agent", "run the improvement pipeline", "apply insights", "/recursive-improve", or when eval/traces/ contains trace files.
llm-wiki
Xây dựng và duy trì knowledge base cá nhân theo pattern LLM Wiki (Karpathy). Hỗ trợ init, ingest, query, lint, discover, run, digest, pain-rank, setup, book-summary, competitive-brief, interview-prep.
alterlab-nmc-multimedia-story
This skill should be used when the user asks about "multimedia storytelling", "interactive story", "longform web feature", "cross-platform narrative", "scrollytelling", "immersive journalism", "act as a multimedia story builder", "multimedia story mode", "web documentary", "transmedia narrative", "visual storytelling", "digital longform", "parallax story", "Shorthand", "Scrollama", "StoryMap", "interactive feature", "Juxtapose", or needs expertise in designing and producing cross-platform narrative experiences for the web. Part of the AlterLab FC Skills collection (New Media & Communication department).
mission-control
Use when Codex should act as the bridge into Mission Control instead of acting like the Manager AI itself.
mission-control-codebase-intake-burst
Use when Mission Control should recommend a read-only codebase intake burst with Repo Mapper, Test Finder, Docs Reader, Risk Scanner, and Dependency Mapper.
mission-control-compiler-autotuning-guidance
Request compiler and autotuning guidance for GPU code through Mission Control with bounded iteration and evidence requirements.
mission-control-cuda-kernel-generation
Route CUDA kernel generation or repair through Mission Control with GPU-aware validation and infrastructure checks.
mission-control-cuda-tile-refactor
Use when CUDA Tile or tile-shaped GPU refactors need Mission Control planning, validation, and benchmark discipline.
mission-control-import
Use when Codex should attach an existing repo or folder to Mission Control and keep the first pass read-only until the user authorizes more.
mission-control-import-codebase
Import or attach an existing codebase into Mission Control. Use when the workspace already contains a repo and Codex should let Mission Control scan, understand, and classify it before edits.
mission-control-install-from-github
Install or repair Mission Control for headless Codex use from a repo checkout or GitHub clone.
mission-control-orchestrate
Use when Codex should route a workspace task through Mission Control instead of acting like the Manager AI.
mission-control-subagent-burst
Recommend or review Mission Control Codex subagent bursts for bounded read-heavy work. Use when the user wants parallel exploration, review, planning, handoff audit, or failure diagnosis without replacing the normal worker system.
azure-networking
Configure Azure VNet, NSG, Load Balancer, and network topology.
loom
Extract requirements from conversations, link to code, detect drift, decompose specs into atomic tasks, and run those tasks on a local small model. Use when making decisions, before modifying code, when a spec is ready for implementation, or to check staleness.
llm-wiki-change
Standard change process for the LLM Wiki engine. Every feature change follows 5 phases: Concept → Verify → Implement → Document → Visualize. Use for any new feature, pipeline change, or script modification. Trigger: "llm-wiki change", "wiki change", "engine change", "neues feature", "pipeline ändern"
sync-process-docs
Sync docs/PROCESS.md with the actual implementation. Reads all scripts, hooks, prompts, and config files, then updates docs/PROCESS.md to reflect reality. Use when scripts have changed, new features were added, or to verify documentation accuracy. Trigger: "sync process docs", "update process", "process docs aktualisieren"
use-llm-wiki
Discover and use a locally-available LLM-wiki through its `wiki` CLI — from any project, not just inside the vault. Read the knowledge base to ground answers in the operator's own compiled knowledge; diagnose pipeline health; contribute back (capture context, record a hard fact, ingest a source); run maintenance (compile, lint, review); or report engine bugs upstream. Step 1 locates the wiki (env var, walk-up, or registry) — if none is found, the skill does not apply and exits cleanly. Use when: an agent in any project should consult, feed, diagnose, or report on the operator's knowledge base — "check the wiki", "what does my wiki say about X", "add this to the wiki", "ingest this", "compile the wiki", "wiki health", "vault status", "is the pipeline healthy", "file a bug against the engine", "report this to lx-0/llm-wiki".
getscribe-site-sync
Audit and re-deploy the getscribe.dev marketing site whenever scribe ships a new release. Use this whenever a new scribe version is tagged or pushed, a new CHANGELOG entry lands, or the user says anything like "sync the site", "update getscribe.dev", "the site is stale", "check the site against the changelog", "did the landing page get updated for this release", or after running `git tag v*`. Also use it proactively when you notice the latest git tag / top CHANGELOG entry is newer than what the site copy reflects. The site is deliberately VERSION-FREE — this skill keeps it factually current with the CHANGELOG while enforcing that no version string ever leaks onto any surface, then deploys to Cloudflare and verifies the live result.
scribe-kb
Read, write, and search a scribe-managed knowledge base (markdown vault with frontmatter conventions, wikilinks, and qmd hybrid search). Use when the user's project has a scribe.yaml (KB root) or a .claude/<kb_name>/ drop-file directory (consumer side), or when they mention scribe, scriptorium, qmd, drop files, or "my KB". Covers frontmatter schema, wikilink syntax, drop-file pattern, search via qmd, and directory taxonomy.
ollama-auto
Auto-delegate cheap text tasks to local Ollama (Mistral) — saves Claude tokens for complex reasoning. Automatically triggers on: large list classification, text formatting/cleaning, output pre-filtering, boilerplate generation, simple text decisions. Includes audit mode to track effectiveness over time. Trigger: "/ollama-auto", "--audit" to see stats, or auto-triggered by Claude on eligible tasks.
context-compress
Guide for using /compact (Claude Code built-in) with the pre-compact save pipeline. Shows what gets saved before compression and what gets reinjected after.
doc-template
Documentation templates - README, API docs, ADRs, user guides
benchmark
Run metric quality benchmark, store results, and compare against previous runs. Invoke with /benchmark, "run benchmark", "benchmark metrics", "check metric quality".
openclaw-memory-graph
Neo4j-backed graph memory for Openclaw providers. Replaces the flat-file `memory/` system with a property graph that supports typed memory nodes, semantic edges, vector-similarity recall, and automatic migration of existing flat-file memories.
eod
Use when /eod is invoked or when Shane wants to close out his day. Diffs Today's Focus vs Session Log, increments deferrals in patterns.md for unlogged tasks, flags items at 3+ deferrals, and writes an EOD Audit to today's daily note.
plan-tomorrow
Use when /plan-tomorrow is invoked or after /eod. Reads today's EOD audit and proposes tomorrow's focus (1 primary, 2 secondary) accounting for known patterns. Writes a Tomorrow block to today's daily note.
qwen-executor
Use this skill to delegate execution-level tasks to a local model via the LiteLLM proxy (default alias `fast-general`, resolving to gemma4:e4b-mlx). Best for: vault skill invocations (/ghost, /challenge, /emerge, /contradict, /drift, /ideas, /trace, /connect, /compound, /bloom, /stranger, /map, /level-up, /learned, /weekly-learnings, /backlinks), file search and summarization, drafting content, and any task where local execution is sufficient and API cost should be minimized. Do NOT use for tasks requiring real-time web access, complex multi-step tool use, or high-stakes decisions.
openclaude-multi-llm
Use Claude Code's full tool system with any OpenAI-compatible LLM — GPT-4o, DeepSeek, Gemini, Ollama, and 200+ models via environment variable configuration.
mission-control-agent-contracts
Show or request Mission Control agent contracts. Use when the user wants to inspect a worker mission, allowed paths, forbidden paths, tools, validation obligations, stop conditions, or escalation rules.
mission-control-agent-graph-workflows
Design graph-style agent workflows with nodes, edges, gates, retries, checkpoints, and human approvals through Mission Control.
mission-control-agent-stuck
Diagnose a stuck Mission Control agent. Use when an agent shows no output, repeats errors, times out, asks for the same approval repeatedly, or stops making progress events.
mission-control-agents-md
Generate or review AGENTS.md from Mission Control understanding. Use when the user wants AGENTS.md proposed from the codebase map, existing instructions reviewed, or a safe draft prepared before writing.
mission-control-api-provider-mode
Use or explain API-provider mode through Mission Control. Use when the user explicitly wants API-backed execution, needs billing implications explained, or wants confirmation that configured secret storage rather than chat-provided keys will be used.
mission-control-approve
Relay Mission Control approvals and questions to the user. Use when there are pending command approvals, tool approvals, write permissions, Manager questions, swarm approvals, recovery decisions, or handoff review gates.
mission-control-autowire-providers
Use when Codex should detect and safely autowire local Mission Control runners without enabling unsafe billing paths by default.
mission-control-benchmark-comparison
Compare before-and-after performance evidence through Mission Control without turning benchmark claims into theater.
mission-control-brand-comms
Coordinate brand-guideline, internal-communications, announcement, and stakeholder-message work through Mission Control with tone, audience, and evidence constraints.
mission-control-bridge
Use when Codex should relay user intent to Mission Control instead of acting as the Manager itself.
mission-control-change-request
Run a post-handoff or mid-project Mission Control change request flow. Use when the user wants additional work classified, impact-estimated, task-created, validated, and folded into the current handoff or milestone safely.
mission-control-claude-cli-mode
Use or prefer Claude CLI runner mode through Mission Control. Use when the user explicitly wants Claude CLI if configured and Codex should verify availability and fallback rather than assuming setup exists.
mission-control-codebase-knowledge-graph
Build or inspect a Mission Control codebase knowledge graph. Use for file/function/class maps, dependency relationships, architectural layers, guided tours, and searchable understanding.
mission-control-codex-cli-mode
Use or prefer Codex CLI runner mode through Mission Control. Use when the user wants Codex CLI as the runner, needs its status explained, or wants the distinction between subscription auth and API-based providers kept clear.
mission-control-conflict-resolution
Resolve Mission Control agent or merge conflicts safely. Use when paths overlap, outputs disagree, or Mission Control needs a user-visible conflict-resolution path instead of hidden reassignment.
mission-control-context-pack
Show or build Mission Control context packs for agents. Use when the user wants to know which files, docs, and constraints are being packaged for a task, why they were selected, and where context coverage is still missing.
mission-control-continue-handoff
Continue work after a Mission Control handoff without losing continuity. Use when the user wants another iteration, wants limitations preserved, or needs the next change request to build on the previous handoff and evidence.
mission-control-creative-web-artifacts
Plan creative web artifacts, themed pages, demos, and visual prototypes through Mission Control while preserving project guardrails and validation.
mission-control-debug
Diagnose stuck or failed Mission Control orchestration. Use when runs are blocked, failing repeatedly, waiting too long, missing evidence, or unclear about the next recovery step.
mission-control-decision-ledger
Show important Mission Control decisions and assumptions. Use when the user wants to review user decisions, Manager assumptions, auto-decisions, rejected options, or approval history without searching raw events.
mission-control-diff-impact
Analyze the impact of current changes or a pull request through Mission Control. Use for ripple effects, affected tests, ownership, risk, and review focus.
mission-control-docs-heavy
Switch the project toward documentation-heavy Mission Control work. Use when the user wants the swarm or plan to prioritize README, guides, examples, docs review, or public-facing written material more than feature code.
mission-control-document-workflow
Coordinate document, PDF, Word, slide, spreadsheet, and report workflows through Mission Control. Use for document generation, conversion plans, extraction, validation, and evidence-backed summaries.
mission-control-domain-map
Extract business domains, flows, process steps, and domain vocabulary from a codebase or knowledge base through Mission Control.
mission-control-evals-observability
Design or run evaluation, tracing, callback, telemetry, and regression-observability workflows for Mission Control agents.
mission-control-event-digest
Summarize recent Mission Control events without raw logs. Use when the user wants the last 5 minutes, last 15 minutes, since last interaction, or since orchestration start summarized in bridge-safe markdown.
mission-control-evidence-check
Check whether Mission Control claims have backing evidence. Use when the user wants to know whether tests, builds, screenshots, artifacts, or handoff confidence are real, missing, weak, or dry-run only.
mission-control-existing-repo-fix
Run a direct Mission Control fix workflow for an existing repo. Use when the task is a bugfix or targeted change in a non-empty codebase and the Manager should classify the request, plan narrowly, request write permission, and execute safely.
mission-control-explain-codebase
Explain an unfamiliar codebase from Mission Control understanding. Use when the user wants stack detection, structure, entry points, how it likely runs, how tests work, risky areas, or recommended exploration next.
mission-control-failure-diagnosis-burst
Use when Mission Control should recommend a read-only failure diagnosis burst across logs, recent changes, tests, dependencies, and recovery planning.
mission-control-generate-runbook
Generate an operational runbook through Mission Control. Use when the user wants RUNBOOK.md or a chat-native runbook covering startup, tests, build, debugging, local reset, logs, and deployment notes.
mission-control-github-ready-docs
Prepare Mission Control docs for public GitHub. Use when documentation should be cleaned for publication, internal AI notes removed, secrets and private paths scrubbed, and install or run guidance made public-ready.
mission-control-handoff
Retrieve and present the final Mission Control handoff. Use when the user asks for the finished result, final summary, what changed, how to run it, evidence, limitations, or next tasks.
mission-control-handoff-audit-burst
Use when Mission Control should recommend a read-only handoff audit burst for run instructions, validation evidence, limitations, docs quality, and security caveats.
mission-control-headless-health
Use when Codex should diagnose Mission Control plugin, daemon, MCP, runtime, or runner health from chat without opening the standalone app.
mission-control-interview
Run a full Mission Control Manager interview. Use when the project is ambiguous, project-specific intake matters, or the user wants the Manager to ask clarifying questions with budgeted depth before planning or build work.
mission-control-keras-finetuning
Route Keras fine-tuning and transfer-learning work through Mission Control with explicit baseline, unfreeze, and evaluation steps.
mission-control-keras-tuning
Route KerasTuner and other bounded hyperparameter searches through Mission Control with explicit budgets and evidence.
mission-control-knowledge-base-map
Build or inspect a graph-style map of docs, wiki pages, claims, entities, and relationships through Mission Control.
mission-control-local-first
Switch Mission Control toward local-first behavior. Use when the user wants local files, local models, no cloud deployment, and no external APIs unless explicitly approved.
mission-control-manager
Manager behavior for Codex Mission Control projects. Use when the manager needs to restate a project idea, run an interview, refine plans, create worker tasks, route follow-up work, or prepare final handoff notes.
mission-control-mcp-builder
Design, build, or audit MCP servers and tool/resource/prompt contracts through Mission Control. Use for MCP schemas, stdio startup, auth boundaries, plugin packaging, and smoke tests.
mission-control-memory-state-policy
Define memory, state, checkpoints, resumability, and retention policy for Mission Control workflows and agents.
mission-control-model-policy
Inspect or update Mission Control model-assignment policy. Use when the user wants to understand or change cost-saving, balanced, best-quality, local-first, or custom model routing across Manager, coding, docs, review, and fallback roles.
mission-control-nsight-profiling
Coordinate Nsight-based GPU profiling through Mission Control with safe evidence capture and approval-aware command use.
mission-control-resume
Use when a new Codex chat needs to reconnect to a recent Mission Control orchestration safely.
mission-control-review-burst
Use when Mission Control should recommend a bounded read-only review burst across correctness, security, testing, maintainability, and docs.
mission-control-review-handoff
Use when Codex should retrieve Mission Control status, evidence, and final handoff notes for review with the user.
mission-control-safe-mode
Use when the user wants Mission Control to operate in a stricter approval-heavy safety posture.
mission-control-status
Use when the user wants a compact Mission Control status summary, blocker report, or agent activity check.
mission-control-swarm
Use when the user wants to inspect or adjust Mission Control swarm strategy from Codex chat.
mission-control-uninstall
Use when Codex should remove the Mission Control plugin bundle, synced skills, and managed Codex MCP registration.
mission-control-update
Use when Codex should refresh an existing Mission Control install, resync the plugin and skills, and rerun headless repair/bootstrap.
wiki_semantic_link
Automatically builds semantic links between concept markdown files by calculating vector similarity using a local Ollama embedding model.
ai-jury
Convene a cross-vendor multi-agent review jury on a diff, PR, or issue and produce one report — Claude Code, Codex, Antigravity, and/or a free local/open-weight model each review independently, cross-examine each other, verify, and reach one verdict — a chair's synthesis or a panel vote. Handles the whole flow end to end (scaffold config if needed → review → report → summarize). Use when the user wants a multi-model review of a pull request, a diff, an issue, or the current branch, or says "review jury", "convene the jury", or "cross-model review".
opengork
Uncensored AI agent with dual backend support. Use Local Heretic mode (Ollama) for 100% uncensored responses, or xAI API for cloud-based inference with partial filtering. Modes: heretic (uncensored), savage (brutal honesty), based (raw opinions), genius (expert analysis), chaos (wild creativity).
planning-in-background
Orchestrates multiple AI agents (Claude, Codex, Gemini) for parallel planning in the background with auto-save. Agents continue running even when session hits context limits. Use for "백그라운드 기획", "bg plan", "병렬 기획", "멀티 AI 기획", "기획해줘", "N명이 기획", "계획", "플래닝", "plan", "설계" requests.
git-workflow
Git workflow rules for Renfield. Commit message format, issue numbering, branch naming, PR creation, documentation updates before push. Triggers on "commit", "push", "PR erstellen", "pull request", "branch", "git", "merge".
doctor
Use before any kagura-engineer run/review/goal, or when the harness reports a blocked environment — diagnoses the local setup (git, claude, gh, ollama, memory backend, gh-issue-driven plugin) by shelling out to `kagura-engineer doctor` and reports what must be fixed.
setup
Use when kagura-engineer:doctor reports a blocked or failing environment — installs and authenticates the harness prerequisites (git, claude, gh, ollama models, memory-cloud auth) by shelling out to `kagura-engineer setup`, then re-checks with doctor.
graphify
Graphify workflow for Pi/Codeflare. Build, refresh, query, explain, trace, or locate repo/Vault/session knowledge. Uses official Graphify AST/build/cluster/report/export flows, and uses the Pi main session agent for semantic extraction and community labels.
rb-ollama
Multi-model AI coding assistant with 51 tools and 13+ providers. Use for code review, refactoring, testing, documentation, and general coding tasks.
compress-prompt
Use when about to write a long prompt, include verbose text in context, or when any block of text needs to be made token-efficient before use. Delegates compression to a local model via the LiteLLM proxy (ollama-agent MCP).
git-clone
Clone a git repository into the workspace. When user asks to clone a repo, output the exact shell command wrapped in a code block so the system can execute it.
rlm-curator
Knowledge Curator agent skill for the RLM Factory. Auto-invoked when tasks involve distilling code summaries, querying the semantic ledger, auditing cache coverage, or maintaining RLM hygiene. Supports both Ollama-based batch distillation and agent-powered direct summarization. V2 enforces Concurrency Safety constraints.
recall-context
Use at the start of orchestrator turns and before dispatching specialists. Queries the Cognee KG+RAG MCP server for the current repo's dataset and returns structured context (decisions, runbooks, glossary terms, adjacent specs) that the orchestrator folds into the next subagent's prompt. Do NOT use inside leaf executors — the orchestrator pre-loads recall and passes it down.
engram-consolidate
Compress and prune Engram memory after long sessions or when the store feels cluttered
engram-diagnose
Inspect a memory for conflicts and evidence, aggregate memory counts by category, or force-summarize a memory
engram-episodes
Start, end, list, and recall named work session episodes in Engram memory
engram-ingest
Bulk-load files, directories, or exported chat histories into Engram; export memories to markdown
model-sovereignty
This skill should be used when the user asks about "local models", "custom models", "fine-tuning", "self-hosting models", "model selection", "which model should I use", "data privacy and models", "LoRA", "RAG vs fine-tuning", "Ollama", "vLLM", or wants guidance on whether to build, host, or customise their own AI models.
ai-friendly-web-design
Guidelines for building AI-accessible web interfaces that work well with AI agents, automation tools, and screen readers. Use this skill whenever the user is building or reviewing a webpage, UI component, form, or frontend feature and any of these apply: they mention AI agents, automation, Playwright, web scraping, accessibility, a11y, aria, semantic HTML, or ask how to make their UI "agent-friendly", "AI-friendly", or "machine-readable". Also trigger when reviewing existing frontend code for accessibility or automation compatibility issues, even if the user doesn't explicitly mention AI.
model-tampering
AI model supply chain attack methodology covering weight tampering, malicious fine-tuning backdoor insertion, plugin/extension hijacking, and model provenance verification bypass. For authorized assessments of AI deployment pipelines.
azure-networking
Configure Azure VNet, NSG, Load Balancer, and network topology.
coldbox-ai-integration
Use this skill when integrating AI capabilities into a ColdBox application using the BoxLang AI library (bx-ai module) -- including simple chat, streaming, pipelines, agents, RAG with vector memory, document loading, tool calling, and injecting the AI service into handlers or models.
draft
Draft wiki pages with a local model (Ollama/LM Studio) into vault/_proposed/ for human review, instead of writing wiki/ directly. Trigger when the user wants free/private/offline drafting, "draft with the local model", or invokes /claude-wiki-pages:draft. Off unless localModel.enabled — Claude Code remains the primary author. Pairs with /claude-wiki-pages:review to promote drafts.
review
Review drafted wiki pages and promote or reject them. Trigger when the user wants to "review proposals/drafts", "approve/reject a draft", check what a local model produced, or invokes /claude-wiki-pages:review. Operates on vault/_proposed/; promotion runs under a git checkpoint and then chains the maintenance loop. The human-in-the-loop gate for any drafted content.
audio-local
当用户发送音频文件或要求语音转文字、音频转录、录音识别时使用此 skill。使用本地 faster-whisper large-v3-turbo 进行语音识别。转录完成后，由 Claude 直接对文本进行总结、分析、翻译等后续处理。触发场景：用户上传音频/录音、要求语音转文字、会议转录、提取音频内容等。
image-local
当用户要求生成图片、画图、创作图像时使用此 skill��使用本地 SDXL Turbo 模型进行文生图，GPU 加速 1 步出图。触发场景：用户说"生成一张图片"、"画一个"、"帮我画"、"generate an image"、"创作一张图"等任何要求用文字生成图片的场景。
vision-local
当用户发送图片、粘贴截图、要求分析/识别/描述图片内容时使用此 skill。使用本地 Ollama minicpm-v:8b 视觉模型分析图片，让纯文本模型具备识图能力。触发场景：用户上传图片、询问图片内容、要求 OCR 提取图中文字、分析截图、描述照片、问"图片里有什么"等。一旦出现图片相关任务，立即使用本 skill，不要尝试直接用 Read 工具读取图片。
rlm
Recursive Language Model loop for large-context tasks. Searches Willow KB first via willow_knowledge_search, then chunks file context and dispatches rlm-subcall (Haiku) per chunk if the KB doesn't fully answer. Use when a query spans more context than fits in the session — corpus archaeology, MIGR1 atoms, large log files, Grove history digests.
data-fetching
Data fetching architecture guide using Service layer + Zustand Store + SWR. Use when implementing data fetching, creating services, working with store hooks, or migrating from useEffect. Triggers on data loading, API calls, service creation, or store data fetching tasks.
ollama-api
Reference skill for Ollama's native `/api/chat` and `/api/show` endpoints. Use when implementing, reviewing, or debugging an Ollama provider that needs chat inference, chat streaming, or full model-information retrieval from Ollama.
Integration detected automatically from skill content. Some results may be false positives.