rjmurillo
UserMulti-agent system for software development
Categories
Indexed Skills (50)
adr-generator
Create comprehensive Architectural Decision Records (ADRs). Researches the destination directory to detect existing template conventions, gathers context, determines next ADR number, generates the ADR, validates completeness, and saves. Supports multiple ADR formats (MADR, Nygard, Alexandrian, project canonical). Use when documenting technical decisions, creating new ADR files, or capturing rationale so future readers can revisit a choice. Use when you say "write an ADR", "document this decision", "document these design choices", "record why we chose this", "capture the rationale", or "for future maintainers", or when creating an ADR-like markdown file under docs/decisions/, docs/adr/, docs/architecture/, architecture/decisions/, or .agents/architecture/. Do NOT use to debate or review an existing ADR (use adr-review).
adr-review
Multi-agent debate orchestration for Architecture Decision Records. Automatically triggers on ADR create/edit/delete. Coordinates architect, critic, independent-thinker, security, analyst, and high-level-advisor agents in structured debate rounds until consensus. Use when you say "review this ADR", when an ADR is created/edited/deleted, or when reviewing, accepting, or updating a decision file under .agents/architecture/, docs/architecture/, docs/decisions/, docs/adr/, or architecture/decisions/, including intent like "review this decision record" or "check this rationale for future maintainers". Do NOT use to author a new ADR (use adr-generator).
analysis-provenance
Identify code ownership before modifying validators or linters. Checks file headers for provenance indicators, reviews documentation, and determines provenance as UPSTREAM, LOCAL, VENDOR, or UNKNOWN. Prevents accidental modification of upstream tools.
analyze
Systematic multi-step codebase analysis producing prioritized findings with file-line evidence. Covers architecture reviews, security assessments, and code quality evaluations through guided exploration, investigation planning, and synthesis. Use when you say "analyze this codebase", "run security assessment", "architecture review of this system", "find code smells", or "review code quality" across multiple files. Do NOT use for single-file maintainability scoring (use code-qualities-assessment) or CWE-78 injection pattern scanning (use security-scan).
benchmark-models
Cross-model benchmark. Runs one prompt or skill through Claude, GPT (Codex CLI), and Gemini side by side and compares latency, tokens, cost, tool calls, and optionally output quality via an Anthropic-API judge. Answers "which model is actually best for this skill?" with data. Use when you say "benchmark models", "compare models", "which model is best for X", "cross-model comparison", or "model shootout". Do NOT use to measure web page performance.
buy-vs-build-framework
Strategic framework for evaluating build, buy, partner, or defer decisions with four-phase process, tiered TCO analysis, and integration with decision quality tools. Use for strategic build/buy/partner/defer with TCO. Do NOT use for "is there an existing library for this" (use programming-advisor).
chaos-experiment
Design and document chaos engineering experiments. Guide steady state baseline, hypothesis formation, failure injection plans, and results analysis. Use when you say "design a chaos experiment", "plan a game day", "failure injection", "test resilience", or "chaos engineering". Do NOT use for security threat analysis (use threat-modeling) or pre-launch project risk identification (use pre-mortem).
chestertons-fence
Investigate historical context of existing code, patterns, or constraints before proposing changes. Automates git archaeology, PR/ADR search, and dependency analysis to prevent removing structures without understanding their purpose. Use when you ask "why does this code/constraint exist", "is it safe to remove this". Do NOT use for forward-risk analysis (use pre-mortem).
codebase-documenter
Scaffold project documentation (README, ARCHITECTURE, API, CODE_COMMENTS) from templates with documented standards. Use when bootstrapping docs for a new or under-documented codebase.
context-optimizer
Analyze skill content for optimal placement (Skill vs Passive Context vs Hybrid), compress markdown to pipe-delimited format (60-80% token reduction), and validate compliance against the decision framework. Based on Vercel research showing passive context achieves 100% pass rates vs 53-79% for skills. Use when you ask "compress this skill", "Skill vs Passive Context placement", "reduce tokens". Do NOT use for gathering knowledge before a task (use context-gather).
cva-analysis
Systematic abstraction discovery using Commonality Variability Analysis. Build matrix of what varies vs what's constant, then let patterns emerge. Prevents wrong abstractions by deferring pattern selection until requirements are analyzed. Use when facing multiple similar requirements and need to discover natural abstractions.
cynefin-classifier
Classify problems into Cynefin Framework domains (Clear, Complicated, Complex, Chaotic, Confusion) and recommend appropriate response strategies. Use when unsure how to approach a problem, facing analysis paralysis, or needing to choose between expert analysis and experimentation.
encode-repo-serena
Populates the Forgetful knowledge base using Serena's LSP-powered symbol analysis for accurate, comprehensive codebase understanding. Use when you say "encode this repository", "populate forgetful with this codebase", "onboard to this repo", "refresh project understanding", or "build knowledge base for this project". Do NOT use to analyze existing repo structure (use serena-code-architecture) or for symbol-edit guidance (use using-serena-symbols).
exploring-knowledge-graph
Guidance for deep knowledge graph traversal across memories, entities, and relationships. Use when needing comprehensive context before planning, investigating connections between concepts, or answering "what do you know about X" questions.
fix-markdown-fences
Repair malformed markdown code fence closings. Use when you say "fix markdown fences", "repair code block closings", "markdown rendering broken", "code blocks bleeding into content", or "validate markdown code blocks" on any .md file. Do NOT use for documentation accuracy checks or verifying code examples (use doc-accuracy).
github-url-intercept
BLOCKING INTERCEPT: When ANY github.com URL appears in user input, STOP and use this skill. Never fetch GitHub HTML pages directly - they are 5-10MB and will exhaust your context window. This skill routes URLs to efficient API calls (1-50KB). Triggers on: pull/, issues/, blob/, tree/, commit/, compare/, discussions/. Use when you paste a GitHub URL, say "analyze this PR", "look at this issue", or "what does this commit do". Do NOT use for creating PRs, posting comments, or adding labels (use github instead).
github
Execute GitHub operations (PRs, issues, milestones, labels, comments, merges) using Python scripts with structured output and error handling. Use when working with pull requests, issues, review comments, CI checks, or milestones instead of raw gh.
guard-maturity
Classify push guards by Hook Maturity Model tier. Aggregates EVENT lines emitted by push_guard_base.py and assigns each guard a tier (Budding, Growing, Mature, Proficient, Inert, Harmful) based on age, intercept count, and fitness derived from block rate. Use to decide when to promote a new guard, when to prune dead weight, and when to remove a harmful one. Triggers `guard maturity report`, `classify push guards`, `hook maturity tiers`.
memory-documentary
Generate evidence-based documentary reports by searching across all 4 memory systems (Claude-Mem, Forgetful, Serena, DeepWiki), .agents/ artifacts, and GitHub issues. Produces investigative journalism-style analysis with full citation chains. Use when you ask for an "evidence-based report", "investigate across all memory systems", "what happened with X over time". Do NOT use for a single semantic recall (use memory) or for citation hygiene (use memory-enhancement).
memory-enhancement
Manage memory citations, verify code references, and track confidence scores. Use when adding citations to memories, checking memory health, or verifying code references are still valid. Use when you say "add a citation", "verify this memory's code refs", "check memory health". Do NOT use for searching or creating memories (use memory) or for documentary reports (use memory-documentary).
memory-gate
Memory-First Gate (BLOCKING) and the Chesterton's Fence investigation protocol, split out of the memory router per ADR-063. Forces a memory search before you change existing code, constraints, or protocol, so the "why" is recovered before the fence comes down. Use when you say `memory-first gate`, `search memory before changing`, or `chesterton fence check`. Do NOT use for plain Tier 1 lookups (use memory-search) or recording a session (use memory-reflexion).
business-strategy
Route a founder problem to the right business framework, then load that framework on demand. Distills 14 business books (customer discovery, positioning, pricing, sales, growth, persuasion) into scored, decision-tree skills. Use when you say diagnose my business problem, what framework applies, how do I validate demand, price this, position this, generate leads, or close deals. Do NOT use for software design (use the engineering rules) or for a single named decision (use decision-critic).
autoplan
Route any request to the right skill, command, or agent chain with defaults, so nobody hand-picks from the full catalog. Use when you say `/autoplan`, `do it`, `handle it`, `figure this out`, or when a concrete request names no skill. Do NOT use when the user names a specific skill or lifecycle command; invoke that directly.
ai-agents-build-and-env
Runbook to recreate the ai-agents dev environment from scratch and survive its traps, including the uv-pinned Python 3.14.6, git hooks install, MCP layer setup, contributor commands, and PEP 668. Use when you say `set up this repo`, `bootstrap the environment`, `fresh clone setup`, or you hit `ModuleNotFoundError yaml`. Do NOT use for the generation pipeline (use `ai-agents-generation-and-release`) or CI gate evidence rules (use `ai-agents-validation-and-qa`).
book-to-skill
Input adapter that extracts a book's method into a structured payload and hands it off to SkillForge. Use when an operator wants to turn a methodology-bearing book (The Mom Test, Make It Stick, Influence, The Pragmatic Programmer, etc.) into one or more executable skills without hand-crafting the SkillForge prompt or bypassing SkillForge's triage and review gates.
code-qualities-assessment
Assess code maintainability through 5 foundational qualities (cohesion, coupling, encapsulation, testability, non-redundancy) with quantifiable scoring rubrics. Works at method/class/module levels across multiple languages. Produces markdown reports with remediation guidance. Use when you ask to "assess maintainability", "score cohesion/coupling/testability" on specific code. Do NOT use for a full pre-merge review (use review) or repo-wide domain grading (use quality-grades).
codeql-scan
Execute CodeQL security scans with language detection, database caching, and SARIF output. Use when performing static security analysis on Python or GitHub Actions code.
context-gather
Gather comprehensive context from Forgetful Memory, Context7 docs, DeepWiki, and web sources before planning or implementation. Follows the exploring-knowledge-graph skill to search across all knowledge tiers and returns a focused summary with a parseable CONTEXT_LOADED marker for downstream skip detection. Use when you say "gather context before planning", "what do we know before I start". Do NOT use for compressing or placing skill text (use context-optimizer).
curating-memories
Guidance for maintaining memory quality through curation. Covers updating outdated memories, marking obsolete content, and linking related knowledge. Use when memories need modification, when new information supersedes old, or when building knowledge graph connections.
decision-critic
Structured decision critic that systematically stress-tests reasoning before commitment surfacing hidden assumptions verifying claims and generating adversarial perspectives to improve decision quality. Do NOT use to surface failure risks pre-launch (use pre-mortem) or to probe why a constraint exists (use chestertons-fence).
doc-accuracy
Multi-phase documentation verification treating code as source of truth. Use when you say "check documentation accuracy", "verify code examples compile", "audit docs vs code", "check doc consistency", or "run doc-accuracy". Use for pre-release doc audits and checking behavioral claims. Do NOT use for broad codebase analysis (use analyze) or fixing markdown fence syntax (use fix-markdown-fences).
execution-plans
Manage execution plans as versioned artifacts with progress tracking and decision logs. Use when you say "create execution plan", "update plan progress", "log decision", "complete plan", or "abandon plan". Do NOT use to break work into milestones or delegate tasks (use planner).
git-advanced-workflows
Advanced Git workflows including rebasing, cherry-picking, bisect, worktrees, and reflog. Use when managing complex Git histories, collaborating on feature branches, or recovering from repository issues.
golden-principles
Scan repository for golden principle violations with agent-readable remediation. Enforces GP-001 through GP-008 from .agents/governance/golden-principles.md. Use when auditing compliance, preparing PRs, or running garbage collection scans.
ai-agents-diagnostics-toolkit
Catalog of this repo's measurement instruments, each with command, current baseline, and interpretation guide. Covers skill size and description budgets, orphan-ref and golden-principles scans, drift gates as signals, guard telemetry and maturity tiers, coverage pins, and the eval harness. Use when you say `measure this`, `read the drift signal`, `check skill budgets`, `guard maturity report`. Do NOT use to fix what you measure (use `ai-agents-debugging-playbook`) or for evidence standards (use `ai-agents-validation-and-qa`).
ai-agents-generation-and-release
Operate the ai-agents generation and release machinery, covering the seven build_all.py generators, generate_agents.py, sync_plugin_lib.py, the drift gates, three plugin.json semver bumps, and the npm publish path. Use when you say `regenerate the mirrors`, `run the drift checks`, `bump the plugin version`, `release the npm cli`. Do NOT use for environment setup (use `ai-agents-build-and-env`) or architecture rationale (use `ai-agents-architecture-contract`).
ai-agents-debugging-playbook
Symptom-to-triage playbook for this repo's recurring failures. Blocked pushes, drift gate reds, plugin bump reds, coverage pin trips, hook exit 143, session NON_COMPLIANT. Maps each symptom to a first command, discriminating experiment, fix path, and trap. Use when you say `triage this failure`, `why is my push blocked`, `debug this CI red`. Do NOT use for incident history (use `ai-agents-failure-archaeology`) or measurement tools (use `ai-agents-diagnostics-toolkit`).
ai-agents-empirical-probe-toolkit
Prove-it methods for this repo. Six recipes for runtime-contract probes, guard and threshold calibration, eval A/B, docs-vs-reality audits, reproduce-on-main CI triage, and negative-control test design, each with a worked example from repo history. Use when you say `probe the runtime contract`, `calibrate this guard`, `prove it empirically`. Do NOT use for the portability battle plan (use `ai-agents-portability-campaign`) or evidence standards (use `ai-agents-validation-and-qa`).
ai-agents-external-claims
Verify external, vendor, and third-party claims (numbers, attributions, structure) against authoritative primary sources before they land in a repo artifact or external deliverable. Covers stake-holding sources, round-number tells, citation-chain drift, and the walk-the-gate-or-file-conservative discipline. Use when you say `verify an external claim`, `check a vendor number`, `is this stat real`, `validate a third-party citation`. Do NOT use for running an experiment (use `ai-agents-research-methodology`) or command-injection scanning (use `security-scan`).
ai-agents-failure-archaeology
The chronicle of this repo's settled battles. Maps each major incident to symptom, root cause, evidence path, and the artifact that fixed it, so nobody re-fights a decided question. Use when you say `has this failed before`, `why does this rule exist`, `failure archaeology`, `what happened with issue 2205`. Do NOT use for triaging a live failure (use `ai-agents-debugging-playbook`) or for extracting learnings from the current session (use `retrospective`).
ai-agents-portability-campaign
Execute cross-harness hook changes for Claude Code and GitHub Copilot CLI using the settled official contract, versioned probes, generators, and runtime tests. Use for `run the portability campaign`, `port hooks to a new harness`, `copilot hook timeout regression`, or `new copilot cli release, recheck the contract`. Do NOT use for fact lookup alone (use `agent-harness-reference`).
ai-agents-research-frontier
Three ranked open research programs for this repo, each with honest current-state evidence, first concrete steps, and a falsifiable milestone. Verified governance (ADR-069, proposed), cross-harness abstraction (ADR-072 and ADR-068, proposed), and the self-improving loop (issue #1345). Use when you say `research frontier`, `open problems`, `what should we research next`. Do NOT use for how to run an experiment here (use `ai-agents-research-methodology`).
ai-agents-research-methodology
How a hunch becomes an accepted result in this repo. Covers the evidence bar, hypothesis-predicts-numbers discipline, and the idea lifecycle from contradiction log through probe, eval baseline, ADR debate, calibrated gate, and guard-maturity monitoring. Use when you say `how do I prove this idea`, `run the idea lifecycle`, `what is the evidence bar`. Do NOT use for the open research programs (use ai-agents-research-frontier) or probe recipe depth (use ai-agents-empirical-probe-toolkit).
ai-agents-validation-and-qa
What counts as evidence in ai-agents and how to produce it. Covers the TESTING-RIGOR pos+neg+edge bar, test layout and collection reality, coverage proof commands, runtime-contract tests with negative controls, and ADR-034 QA skip semantics at session end. Use when you say `what counts as evidence`, `how do I test this change`, `run skill tests`, `can I skip QA`. Do NOT use for CI failure triage (use `ai-agents-debugging-playbook`) or measurement tooling (use `ai-agents-diagnostics-toolkit`).
ai-agents-change-control
Change control for this repo. Classify a change (docs-only, investigation-only, code, plugin content, hook, workflow, ADR governance), map each class to the gates it triggers, and hold the non-negotiables with the incident behind each rule. Use when you say `classify this change`, `what gates does this change trigger`, `which rules are non-negotiable`. Do NOT use for producing test evidence (use `ai-agents-validation-and-qa`) or incident history (use `ai-agents-failure-archaeology`).
ai-agents-architecture-contract
Load-bearing design decisions for this repo as a contract you check before changing anything. Covers the asymmetric generation seam, source-of-truth per tree, hook runtime failure policy, memory tiers, plugin surfaces, invariants, and known-weak points. Use when you say `which tree is canonical`, `architecture contract`, `why is this designed this way`. Do NOT use for operating the build pipeline (use `ai-agents-generation-and-release`) or CI triage (use `ai-agents-debugging-playbook`).
ai-agents-config-catalog
Catalog of every configuration axis in this repo, env vars, commit markers, frontmatter keys, QA skip verdicts, and escape hatches, each with its enforcement point and abuse story, plus the checklist for adding a new flag safely. Use when you say `what does a skip flag do`, `list escape hatches`, `can I skip this gate`, `add a config flag`. Do NOT use for hook runtime behavior (use `agent-harness-reference`) or change gating policy (use `ai-agents-change-control`).
ai-agents-docs-of-record
Runbook for this repo's documents of record. Session logs, ADRs, retrospectives, Serena memories, per-issue handoffs, plus the templates, validators, naming rules, and house prose style that bind them. Use when you say `write the session log`, `create an ADR`, `fill the retro`, `save this to memory`, `which document of record`. Do NOT use for authoring skills (use `SkillForge`) or research write-ups (use `ai-agents-research-methodology`).
agent-harness-reference
Field reference for Claude Code and GitHub Copilot CLI hook contracts. Covers hook locations, events, matchers, payloads, decisions, exit codes, timeouts, plugin roots, and cloud limits with official URLs and versioned probes. Use for `harness contract`, `copilot cli hook behavior`, `hook payload format`, `stale plugin root`, `Errno 2 _dispatch.py`, or before changing cross-harness hooks. Do NOT use to run the porting campaign (use `ai-agents-portability-campaign`).
avoiding-manufactured-work
Detect and stop manufactured work after a deliverable appears done. Use when a worker has produced a plan, issue, PR, backlog item, research artifact, or follow-up task and you need to verify it was demanded by a real user, acceptance criterion, or blocked decision instead of reward-seeking activity.
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.