LangChain
AICommonly used with
Skills using LangChain (613)
cloudbase
Use this skill when you develop, design, build, deploy, debug, migrate, or troubleshoot CloudBase (腾讯云开发, 云开发, TCB, 微信云开发) projects — Web, 微信小程序, 小程序, uni-app, mobile (iOS, Android, Flutter, React Native). Covers UI (页面, 界面, 表单, dashboard, prototype, 原型); auth (登录, 注册, OAuth, publishable key); databases (NoSQL 文档数据库, MySQL 关系型数据库, PostgreSQL/CloudBase PG, app.rdb(), queryPgDatabase/managePgDatabase, CRUD, security rules); 云函数/cloud functions (serverless, scf_bootstrap); CloudRun (云托管, Dockerfile); 云存储; built-in AI (内置大模型, AI 对话, streaming, 流式输出, 图片生成, generateText, streamText, createModel, generateImage, TokenHub, Hunyuan, DeepSeek, GLM, Kimi, Token Credits 资源包, 小程序成长计划); third-party/custom model onboarding (第三方大模型接入, 大模型调用, LLM API); AI agent (智能体, AG-UI, LangGraph); ops troubleshooting (巡检, 诊断, 日志); spec workflow (需求文档, 技术方案, requirements, tasks.md). Do NOT use for non-CloudBase projects, pure frontend without CloudBase, or self-hosted backends without CloudBase.
autogpt-agents
Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.
crewai-multi-agent
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.
langchain
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.
llamaindex
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.
meta-theory
Meta_Kim executable governance dispatcher. It classifies the run, loads only needed references, preserves foundational capabilities and runtime-native abilities, routes owner + weapon + dependency + runtime + OS + verification, and closes only with evidence, intent acceptance, and writeback decision.
cloudbase-agent
Build and deploy AI agents with CloudBase Agent SDK (TypeScript & Python). Implements the AG-UI protocol for streaming agent-UI communication. Use when deploying agent servers, using LangGraph/LangChain/CrewAI adapters, building custom adapters, understanding AG-UI protocol events, or building web/mini-program UI clients. Supports both TypeScript (@cloudbase/agent-server) and Python (cloudbase-agent-server via FastAPI).
code-review
Perform comprehensive code reviews focusing on best practices, security vulnerabilities, performance optimization, and maintainability
data-visualization
Create effective data visualizations using best practices for clarity, accuracy, and visual communication of insights
financial-analysis
Perform comprehensive financial analysis including DCF modeling, ratio analysis, and financial statement evaluation for companies and investment opportunities
build-dashclaw
Contribute to the DashClaw codebase — architecture, scaffolding, tests, CI
create-policies
Create and test DashClaw guard policies for agent governance
instrument-agent
Integrate DashClaw SDK into any agent using the 4-step governance loop
manage-approvals
Human-in-the-loop approval workflows for governed agent actions
register-on-dashclaw
Register any agent (including this one) as a governed agent on a DashClaw instance
setup-dashclaw
Set up a DashClaw instance, install the CLI tool, and configure Claude Code hooks
troubleshoot
Debug DashClaw errors, signal issues, and misconfigurations
rag-architect
Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality. Use when building RAG systems, vector databases, or knowledge-grounded AI applications requiring semantic search, document retrieval, context augmentation, similarity search, or embedding-based indexing.
denario
Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
sap-cloud-sdk-ai
Integrates SAP Cloud SDK for AI into JavaScript/TypeScript and Java applications. Use when building applications with SAP AI Core, Generative AI Hub, or Orchestration Service. Covers chat completion, embedding, streaming, function calling, content filtering, data masking, document grounding, prompt registry, and LangChain/Spring AI integration. Supports OpenAI GPT-4o, Llama, Gemini, Amazon Nova, and other foundation models via SAP BTP.
sap-cloud-sdk-ai-python
Integrates the SAP Cloud SDK for AI for Python (sap-ai-sdk-gen, formerly generative-ai-hub-sdk) into Python applications. Use when building Python apps with SAP AI Core, Generative AI Hub, or the Orchestration Service: chat completion, embeddings, streaming, LangChain integration, templating, content filtering, data masking, and document grounding. Supports OpenAI GPT models, Llama, Gemini, Amazon Nova, and other foundation models via SAP BTP.
accessibility
Accessibility patterns for WCAG 2.2 compliance, keyboard focus management, React Aria component patterns, cognitive inclusion, native HTML-first philosophy, and user preference honoring. Use when implementing screen reader support, keyboard navigation, ARIA patterns, focus traps, accessible component libraries, reduced motion, or cognitive accessibility.
agent-orchestration
Agent orchestration patterns for agentic loops, multi-agent coordination, alternative frameworks, and multi-scenario workflows. Use when building autonomous agent loops, coordinating multiple agents, evaluating CrewAI/AutoGen/Swarm, or orchestrating complex multi-step scenarios.
ai-ui-generation
AI-assisted UI generation patterns for json-render, v0.app, Google Stitch, Bolt Cloud, and Cursor workflows. Covers prompt engineering for component and full-stack app generation, review checklists for AI-generated code, design token injection, refactoring for design system conformance, and CI gates for quality assurance. Use when generating UI components with AI tools, rendering multi-surface MCP visual output, reviewing AI-generated code, or integrating AI output into design systems.
analytics
Queries local analytics across OrchestKit projects for agent usage, skill frequency, hook timing, team activity, session replay, cost estimation, and model delegation trends. Privacy-safe with hashed project IDs. Supports time-range filtering and comparative analysis. Use when reviewing performance, estimating costs, or understanding usage patterns.
animation-motion-design
Animation and motion design patterns using Motion library (formerly Framer Motion) and View Transitions API. Use when implementing component animations, page transitions, micro-interactions, gesture-driven UIs, or ensuring motion accessibility with prefers-reduced-motion.
api-design
API contract design for REST and GraphQL, covering resource shape, URL and header versioning with deprecation windows, RFC 9457 Problem Details error handling, and OpenAPI specs. Use when specifying the wire contract an endpoint exposes, choosing a versioning scheme, or standardizing error response bodies across services. Framework-agnostic protocol layer, not runtime implementation.
architecture-decision-record
ADR templates in the Nygard format with context, decision, consequences, and alternatives. Use when writing ADRs, recording an architectural decision, or evaluating options.
architecture-patterns
Architecture validation and patterns for clean architecture, backend structure enforcement, project structure validation, test standards, and context-aware sizing. Use when designing system boundaries, enforcing layered architecture, validating project structure, defining test standards, or choosing the right architecture tier for project scope.
ascii-visualizer
ASCII diagram patterns for architecture, workflows, file trees, and data visualizations. Use when creating terminal-rendered diagrams, box-drawing layouts, progress bars, swimlanes, or blast radius visualizations.
assess
Assesses and rates quality 0-10 across multiple dimensions (correctness, maintainability, security, performance, testability, simplicity) with pros/cons analysis. Compares against project conventions and prior decisions from memory. Produces structured evaluation reports with actionable improvement suggestions. Use when evaluating code, designs, architectures, or comparing alternative approaches.
async-jobs
Async job processing patterns for background tasks, Celery workflows, task scheduling, retry strategies, and distributed task execution. Use when implementing background job processing, task queues, or scheduled task systems.
auto
Intent-classified router, the front door to OrchestKit and the DEFAULT entry point for any goal-shaped request. Classifies a plain-English goal and routes it to the right specialist skill. Routing is never overhead, so use it even when the target skill seems obvious; skip only when already executing inside another skill (no recursion). Triggers on: auto, do this, figure out, just make, I want, help me, fix, build, improve, any goal description.
bare-eval
Run isolated eval and grading calls using CC 2.1.81 --bare mode. Constructs claude -p --bare invocations for skill evaluation, trigger testing, and LLM grading without plugin/hook interference. Use when running eval pipelines, grading skill outputs, benchmarking prompt quality, or testing trigger accuracy in isolation.
brainstorm
Design exploration using parallel agents through a 7-phase process: topic analysis, memory context, divergent ideation (10+ ideas), feasibility filtering, evaluation with devil's advocate scoring (0-10 across 7 dimensions), synthesis of top approaches, and trade-off comparison. Supports open exploration, constrained design, comparison, quick ideation, and iterative optimization modes. Use when brainstorming ideas, exploring solutions, or comparing alternatives.
browser-tools
Security wrapper over the upstream agent-browser skill, adding URL blocklisting, rate limiting, robots.txt enforcement, and scraping guardrails. Use when automating browser workflows that need safety limits.
business-case
Business case analysis with ROI, NPV, IRR, payback period, and TCO calculations for investment decisions. Use when building financial justification, cost-benefit analysis, build-vs-buy comparisons, or sensitivity analysis.
chain-patterns
Chain patterns for multi-phase pipelines: MCP detection, handoff files, checkpoint-resume, worktree agents, CronCreate monitoring. Use when building or debugging a pipeline skill.
checkpoint-resume
Rate-limit-resilient pipeline with checkpoint/resume for long multi-phase sessions. Saves progress to .claude/pipeline-state.json after each phase. Use when starting a complex multi-phase task that risks hitting rate limits, when resuming an interrupted session, or when orchestrating work spanning commits, GitHub issues, and large file changes.
ci-debug
Diagnose a failing CI run against an 11-pattern playbook. Classifies the failure, cites the relevant memory entry, proposes the exact fix command — but NEVER applies without explicit user approval. Use when a specific PR check or GitHub Actions run failed and you want a diagnosis instead of speculation. Don't use for org-wide CI sweeps (that's /status) or for app-level test failures (the playbook is CI-infra-specific).
ci-sentinel
Daily autonomous classifier for failing PRs across your repos. Runs /ci-debug headless against every open PR with red required checks, posts the verdict as a collapsed PR comment, and appends to a per-repo .sentinel/ledger.jsonl. v1 is propose-don't-apply — NEVER auto-pushes a fix. Use when you're tired of /status sweeps catching the same 10 CI failure patterns over and over.
code-review-playbook
Structured review processes, conventional comments, language-specific checklists, and feedback templates. Use when reviewing PRs, conducting code review, or standardizing review practice.
commit
Creates commits with Conventional Commits format (feat/fix/docs/refactor/test/chore), scope detection, co-author attribution, and pre-commit hook compliance. Validates staged changes and prevents secrets or generated-only files from being committed. Use for requests to commit, stage and commit, save progress, or write a commit message. Do not invoke it for incidental git commits during other work; those stay a bare CLI call.
competitive-analysis
Strategic analysis frameworks including Porter's Five Forces (industry attractiveness), SWOT (internal positioning), and competitive landscape mapping with battlecard generation. Produces competitor profiles, feature gap analysis, and positioning recommendations. Use when analyzing market position, evaluating threats, or building sales battlecards.
component-search
Search 21st.dev component registry for production-ready React components. Finds components by natural language description, filters by framework and style system, returns ranked results with install instructions. Use when looking for UI components, finding alternatives to existing components, or sourcing design system building blocks.
configure
Interactive wizard for OrchestKit settings: MCP servers, hook permissions, keybindings, and install presets. Use when customizing plugin behavior or managing settings.
cover
Generate tests that do not exist yet. Analyzes coverage gaps, then writes and runs new test files across three tiers (unit, integration via testcontainers, Playwright E2E), one test-generator agent per tier, healing failures for up to 3 iterations. Use when code has no tests or when raising coverage after implementation. Do NOT use to grade tests that already exist (use /ork:verify) or to run a suite without writing anything new.
create-pr
Creates GitHub pull requests with pre-flight validation, conventional title formatting, and structured summary generation. Runs parallel checks (tests, lint, type-check, security) before opening. Supports feature, bugfix, refactor, and hotfix PR types with milestone assignment via gh CLI. Invoke only if the operator named it; an everyday `gh pr create` stays plain tooling. Use when opening PRs or submitting code for review.
database-patterns
Database design and migration patterns for Alembic migrations, schema design (SQL/NoSQL), and database versioning. Use when creating migrations, designing schemas, normalizing data, managing database versions, or handling schema drift.
demo-producer
Universal demo video creator for skills, agents, plugins, tutorials, CLI commands, and code walkthroughs. Generates scripts, storyboards, VHS terminal recordings, and Remotion video compositions with task-tracked production phases. Use when producing video showcases, marketing content, or terminal recordings.
design-context-extract
Extract design DNA from app screenshots, live URLs, or screen recordings using Google Stitch — color palettes, typography, spacing tokens, component patterns, and motion specs as design-tokens.json or Tailwind config. Use when the user points to a screenshot, URL, or video and asks to extract or audit the design, analyze animations or scroll behavior, or keep new pages matching an established visual identity.
design-import
Scaffolds React components from a Claude Design handoff bundle and stops at files on disk: no stories, no tests, no pull request. Use when handed a claude.ai/design URL or a local bundle file; when that same scaffold should carry on through test generation, browser verification and an opened PR, run /ork:design-ship instead.
design-ship
One-shot pipeline turning a claude.ai/design link into a pull request: scaffold via /ork:design-import, stories and specs via /ork:cover, browser verification via /ork:expect, then open the PR. Use when a design link should come back as a PR with no intermediate steps; if all you need is the components written to disk, run /ork:design-import instead.
design-stylecards
Declarative catalog of named aesthetic recipes — exact shadow stacks, glass surfaces, gradient treatments, and type scales as copy-paste values with Use-When and Avoid rules. Use when the user asks for polished elevation, glassmorphism, a border gradient, a mesh background, or any 'make it look like X' request where taste should come from a versioned recipe instead of being reinvented per session.
design-system-tokens
Design token management with the W3C Design Token spec, three-tier hierarchy (global/alias/component), OKLCH color, Style Dictionary transforms, and dark mode theming. Use when creating token files, implementing theme systems, or building design-to-code pipelines.
design-to-code
Mockup-to-component pipeline using Google Stitch, 21st.dev, and Storybook MCP. Accepts a screenshot, a description, or a URL and produces production-ready React components, checking existing Storybook components before generating anything new. Use when implementing UI from a mockup or screenshot. To call the MCP tool surface on its own, with no design to convert, use storybook-mcp-integration.
dev
One-command dev loop boot. Spins up portless (named HTTPS subdomain), emulate (stateful API mocks), the project's dev server, and an agent-browser session, all keyed to the current git branch. Use when starting a feature branch, switching worktrees, or returning to a project after a break. Skips silently with install hints when prerequisite binaries are missing.
devops-deployment
Use when setting up CI/CD pipelines, containerizing applications, deploying to Kubernetes, or writing infrastructure as code. DevOps & Deployment covers GitHub Actions, Docker, Helm, and Terraform patterns.
distributed-systems
Distributed systems patterns for locking, resilience, idempotency, and rate limiting. Use when implementing distributed locks, circuit breakers, retry policies, idempotency keys, token bucket rate limiters, or fault tolerance patterns.
doctor
OrchestKit doctor for health diagnostics across manifest integrity, hook configuration, skill validation, agent frontmatter, MCP server connectivity, CC version compatibility, and permission rules. Reports issues with severity levels and auto-remediation suggestions. Validates component counts, detects orphaned entries, and checks CC version matrix compliance. Use when diagnosing plugin health, troubleshooting configuration issues, or running pre-release checks.
documentation-patterns
Technical documentation patterns for READMEs, ADRs, API docs (OpenAPI 3.1), changelogs, and writing style guides. Use when creating project documentation, writing architecture decisions, documenting APIs, or maintaining changelogs.
domain-driven-design
DDD tactical patterns for complex business modeling including entities, value objects, aggregates, domain services, repositories, specifications, and bounded contexts. Python dataclass implementations with TypeScript alternatives. Use when building rich domain models, enforcing invariants, or separating domain logic from infrastructure.
dream
Nightly memory consolidation — prunes stale entries, merges duplicates, resolves contradictions, rebuilds MEMORY.md index. Use when memory files have accumulated over many sessions and need cleanup. Do NOT use for storing new decisions (use remember) or searching memory (use memory).
emulate-seed
Generate emulate seed configs for stateful API emulation. Wraps Vercel's emulate tool for GitHub, Vercel, Google OAuth, Slack, Apple Auth, Microsoft Entra, AWS, Okta, Clerk, Resend, Stripe, and MongoDB Atlas APIs — full state machines, not mocks. Use when setting up test environments, CI pipelines, integration tests, or offline development.
errors
Error pattern analysis and troubleshooting for Claude Code sessions. Categorizes errors (network, auth, model, tool, memory, permission) with known resolution patterns, searches memory for prior occurrences, and suggests recovery steps. Delegates to debug-investigator agent for complex root cause analysis. Use when handling errors, fixing failures, or troubleshooting session issues.
expect
Diff-aware AI browser testing — reads the git diff, maps changes to affected pages via the route map, generates a targeted test plan, and executes it via agent-browser (Rust daemon + CDP, ARIA-tree-first) with pass/fail reporting. Use when testing UI changes, verifying PRs before merge, or running regression checks on changed components.
explore
Multi-angle codebase exploration spawning 3-5 parallel agents for code structure, data flow, architecture patterns, and health assessment. Generates ASCII visualizations, import graphs, and design pattern detection with cross-session memory storage. Use when exploring a repo, discovering architecture, onboarding to a new codebase, or analyzing design patterns.
feedback
Manages OrchestKit learning system including feedback status, usage pattern tracking, and privacy/analytics consent. Supports pause/resume learning, data export, privacy policy display, and bug reporting. Tracks learned patterns and agent performance metrics. Use when reviewing learned patterns, pausing learning, or managing data consent.
figma-design-handoff
Figma-to-code design handoff patterns including Figma Variables to design tokens pipeline, component spec extraction, Dev Mode inspection, Auto Layout to CSS Flexbox/Grid mapping, and visual regression with Applitools. Use when converting Figma designs to code, documenting component specs, setting up design-dev workflows, or comparing production UI against Figma designs.
fix-issue
Fixes GitHub issues using parallel analysis agents for root cause investigation, code exploration, and regression detection. Reads issue context from gh CLI, searches codebase and memory for related patterns, generates a fix with tests, and links the resolution back to the issue via PR. Includes prevention analysis to avoid recurrence. Use when debugging errors, resolving regressions, fixing bugs, or triaging issues.
github-operations
GitHub CLI operations for issues, PRs, milestones, and Projects v2. Covers gh commands, REST API patterns, and automation scripts. Use when managing GitHub issues, PRs, milestones, or Projects with gh.
golden-dataset
Golden dataset lifecycle patterns for curation, versioning, quality validation, and CI integration. Use when building evaluation datasets, managing dataset versions, validating quality scores, or integrating golden tests into pipelines.
add-binding-feature
Add or change a public NeMo Relay runtime API across Rust and affected language bindings when no more specific maintainer skill owns the domain. Do not use for middleware additions, internal refactors, binding-local fixes, or docs-only changes.
add-middleware
Add a new NeMo Relay guardrail or intercept type, registration surface, or pipeline stage. Do not use for changing an existing middleware implementation without a new middleware contract.
contribute-docs
Author or edit NeMo Relay documentation or examples when repository-specific MDX, public API, integration, or release-history conventions matter. Do not use for review-only requests or incidental prose edits in code.
karpathy-guidelines
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
maintain-ci
Change or review NeMo Relay GitHub Actions workflows where permissions, pinned actions, caching, reusable workflows, or release gates require repository-specific handling. Do not use for ordinary source changes that merely run in CI.
maintain-dynamic-plugins
Change NeMo Relay dynamic plugin loaders, manifests, native ABI, gRPC worker protocol, or Python worker SDK. Do not use for ordinary built-in plugin configuration.
maintain-observability
Change NeMo Relay event fields, subscribers, ATIF output, or typed OpenTelemetry and OpenInference projections. Do not use for instrumentation examples that leave observability contracts unchanged.
maintain-packaging
Add or change NeMo Relay packages, package metadata, module paths, generated artifacts, registry output, or release-facing build surfaces, including registering new unified-release surfaces with version automation. Do not use for a standalone project version bump, ordinary source builds, or tests.
nemo-relay-debug-runtime-integration
Use this skill when NeMo Relay is installed or imported but application-side runtime behavior is missing or incorrect, including load failures, inactive scopes, missing events, and plugin or adaptive wiring problems.
nemo-relay-get-started
Use this skill when first-time NeMo Relay users want to try Relay, choose the least-complex supported quick start, or verify initial value through the CLI, a maintained integration, or direct Python, Node.js, or Rust instrumentation before production setup.
nemo-relay-install
Use this skill when choosing or running NeMo Relay installation for the CLI, Python, Node.js, Rust, OpenClaw, or maintained framework integrations, or when explaining Hermes Agent's built-in Relay integration.
nemo-relay-instrument-calls
Use this skill when an application owns tool or LLM/provider call sites and needs to wrap them with NeMo Relay scopes and managed execution APIs for lifecycle events, middleware, or guardrails.
nemo-relay-instrument-context-isolation
Use this skill when concurrent requests, async tasks, threads, workers, goroutines, or agents need independent NeMo Relay scope stacks and correct ancestry propagation.
nemo-relay-instrument-typed-wrappers
Use this skill when adding NeMo Relay typed wrappers, domain types, or provider codecs while preserving JSON middleware semantics and caller-visible behavior.
nemo-relay-integrate-upstream
Use this skill when assessing, extending, or implementing NeMo Relay support in an agent harness or agent framework, including coding agents and orchestration runtimes, when the host lacks Relay support or an existing integration needs deeper coverage. It identifies the host's execution boundaries and extension points, selects an appropriate attachment method for each boundary, and verifies the resulting coverage.
nemo-relay-migrate-from-flow
Use this skill when migrating applications, examples, integrations, documentation, manifests, or repository code from NeMo Flow to NeMo Relay across Python, Rust, Node.js, Go, C FFI, CLI, configuration, and observability surfaces.
nemo-relay-plugin-adaptive-tuning
Use this skill when baseline NeMo Relay instrumentation exists and the user wants to configure or evaluate adaptive plugin behavior, including telemetry, state, adaptive_hints, tool_parallelism, ACG, hint consumption, or measured rollout.
nemo-relay-plugin-build
Use this skill when building or packaging reusable NeMo Relay runtime behavior as an embedded configuration component or a manifest-backed `rust_dynamic` native or `worker` gRPC plugin, with deterministic validation and rollback-safe registration.
nemo-relay-plugin-observability
Use this skill when choosing or configuring NeMo Relay 0.6 or 0.7 observability through the built-in plugin, subscribers, or exporters, including raw ATOF events, ATIF trajectories, OpenTelemetry, OpenInference, or custom event handling.
prepare-code-freeze
Execute a requested NeMo Relay code freeze by cutting a release branch, updating nightly alpha configuration, bumping main, and preparing the required PR. Do not use for an ordinary version bump or release-note draft.
prepare-pr
Prepare, create, publish, or edit a NeMo Relay pull request or its body using the repository template and contributor requirements. Do not use for code review or implementation without PR preparation.
test-go-binding
Build and test the NeMo Relay Go binding; use this for go/nemo_relay changes or Go-facing integration checks
test-python-binding
Build and test the NeMo Relay Python binding and worker plugin SDK; use for python/nemo_relay, python/plugin, or crates/python changes
test-rust-core
Build and test NeMo Relay Rust core, adaptive, and dynamic plugin crates; use for crates/core, crates/adaptive, crates/plugin, crates/worker, crates/worker-proto, crates/types, or shared runtime changes
update-project-version
Perform a NeMo Relay project release-version change across project-owned manifests, dependencies, lockfiles, and generated attribution surfaces while keeping just set-version coverage complete. Do not use for dependency-only updates or adding a package when no project version bump is requested.
validate-change
Choose and run the right NeMo Relay validation matrix for a change instead of using one fixed test list
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
adr-drafting
Creates new Architecture Decision Record (ADR) documents for significant architectural changes using a consistent template and repository-aware naming and storage guidance. Use when a user or agent decides on an architectural change, needs to document technical rationale, or wants to add a new ADR to the project history.
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