Claude Code Toolkit — AI Agent Reference

For LLMs operating in this repository. Not Claude Code specific — any AI agent benefits from this.

Inventory date: 2026-03-21. Counts verified against filesystem.

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Repository Map

claude-code-toolkit/
  agents/                  # Domain expert markdown files + INDEX.json
  skills/                  # Skill directories, each with SKILL.md
  hooks/                   # Python event hooks + lib/ shared modules
  scripts/                 # Deterministic CLI tools (Python + shell)
  commands/                # Slash-menu command definitions
  adr/                     # Architecture Decision Records
  docs/                    # Documentation (you are here)
  evals/                   # Evaluation test suites
  templates/               # Scaffolding templates (e.g. reddit/)
  services/                # Service configurations
  tests/                   # Cross-component test suites
  .claude/                 # Repo-local settings (gitignored)
  .local/                  # User overlay directory (gitignored)
  .local.example/          # Overlay templates shipped with repo

Component Inventory

Type	Location	What It Is
Agent	`agents/*.md`	Domain expert. Markdown file with YAML frontmatter. Gets loaded as system prompt when routed to.
Skill	`skills/*/SKILL.md`	Workflow methodology. Phased instructions with gates. Paired with an agent at routing time.
Hook	`hooks/*.py`	Python script triggered by Claude Code lifecycle events. Reads JSON from stdin, outputs JSON to stdout.
Script	`scripts/.py`, `scripts/.sh`	Deterministic CLI tool. No LLM judgment -- pure computation, file ops, API calls.
Command	`commands/*.md`	Slash-menu entry point. Maps `/command-name` to a skill invocation.

Commands

Command	File
`/do`	`commands/do.md`
`/install`	`commands/install.md`
`/pr-review`	`commands/pr-review.md`
`/reddit-moderate`	`commands/reddit-moderate.md`
`/retro`	`commands/retro.md`
`/system-upgrade`	`commands/system-upgrade.md`
`/create-pipeline`	`commands/create-pipeline.md`
`/github-profile-rules`	`commands/github-profile-rules.md`
`/perses-onboard`	`commands/perses-onboard.md`

Architecture

Router --> Agent --> Skill --> Script. The /do skill classifies every request by complexity (Trivial, Simple, Medium, Complex), selects a domain agent from agents/INDEX.json, pairs it with a skill, stacks enhancements (anti-rationalization, TDD, verification), and dispatches. Agents do the thinking. Scripts do the computation. Hooks fire at lifecycle boundaries to inject context, capture learnings, and enforce gates. Everything flows through /do -- it's the single entry point.

Entry Point: `/do`

1. Parse request -> classify complexity (Trivial | Simple | Medium | Complex)
2. Check force-route triggers -> if match, invoke that skill immediately
3. Look up agent in agents/INDEX.json -> fallback to static routing table
4. Pair agent with skill (domain default or task-verb override)
5. Dispatch: agent executes with skill methodology loaded as instructions

Trivial = reading a file the user named by exact path. Everything else routes through an agent.

Hook System

Event Types

Event	When It Fires	stdin Schema	Hook Can Block?
`SessionStart`	Session begins	`{}` (no event data)	No
`UserPromptSubmit`	Before processing user message	`{"type": "UserPromptSubmit", "prompt": "..."}`	No
`PreToolUse`	Before a tool executes	`{"type": "PreToolUse", "tool_name": "...", "tool_input": {...}}`	Yes (exit 2)
`PostToolUse`	After a tool executes	`{"type": "PostToolUse", "tool_name": "...", "tool_input": {...}, "tool_result": {"output": "..."}}`	No
`PreCompact`	Before context compression	`{"type": "PreCompact"}`	No
`TaskCompleted`	Task/subagent finishes	`{"type": "TaskCompleted", ...}`	No
`SubagentStop`	Subagent session ends	`{"type": "SubagentStop", "agent_type": "...", ...}`	Yes (exit 2)
`Stop`	Session ends	`{"type": "Stop"}`	No

Field name difference: Both PreToolUse and PostToolUse use tool_name (not tool). PostToolUse adds tool_result with an output field.

Blocking: Exit code 2 from a PreToolUse or SubagentStop hook prevents the action. Exit 0 = allow. All other events ignore exit codes.

Hook Output Format

{
  "hookSpecificOutput": {
    "hookEventName": "PostToolUse",
    "additionalContext": "injected into system context",
    "userMessage": "displayed verbatim to user"
  }
}

Hook-to-Event Mapping

Hook	Event	Purpose
`sync-to-user-claude.py`	SessionStart	Sync repo to `~/.claude/`
`session-context.py`	SessionStart	Load learned patterns from learning.db
`cross-repo-agents.py`	SessionStart	Discover `.claude/agents/` in other repos
`fish-shell-detector.py`	SessionStart	Detect fish shell, inject bash workarounds
`skill-evaluator.py`	UserPromptSubmit	Inject agent/skill routing hints
`auto-plan-detector.py`	UserPromptSubmit	Inject `<auto-plan-required>` for complex tasks
`retro-knowledge-injector.py`	UserPromptSubmit	FTS5 query learning.db, inject relevant knowledge
`instruction-reminder.py`	UserPromptSubmit	Re-inject CLAUDE.md instructions periodically
`capability-catalog-injector.py`	UserPromptSubmit	Inject available capabilities list
`operator-context-detector.py`	SessionStart	Detect operator context in prompts
`perses-mcp-injector.py`	UserPromptSubmit	Inject Perses MCP context
`pipeline-context-detector.py`	UserPromptSubmit	Detect pipeline state
`confidence-decay.py`	Stop	Decay low-use learning.db entries
`pretool-git-submission-gate.py`	PreToolUse	Block raw `git push`/`gh pr create` (exit 2)
`pretool-creation-gate.py`	PreToolUse	Block Write without ADR for creation tasks
`pretool-learning-injector.py`	PreToolUse	Inject relevant learnings before tool execution
`block-attribution.py`	PreToolUse	Block "Co-Authored-By: Claude" in commits
`perses-lint-gate.py`	PreToolUse	Block Perses writes that fail linting
`post-tool-lint-hint.py`	PostToolUse	Suggest lint fixes after Write/Edit
`error-learner.py`	PostToolUse	Detect errors, record to learning.db
`review-capture.py`	PostToolUse	Capture review agent findings
`retro-graduation-gate.py`	PostToolUse	Check if PR includes retro graduation
`routing-gap-recorder.py`	PostToolUse	Record when /do finds no matching agent
`usage-tracker.py`	PostToolUse	Track skill/agent invocation counts
`agent-grade-on-change.py`	PostToolUse	Re-grade agent after edits
`sapcc-go-detector.py`	SessionStart	Detect SAP CC Go patterns
`user-correction-capture.py`	PostToolUse	Capture when user corrects output
`precompact-archive.py`	PreCompact	Archive learnings before context compression
`task-completed-learner.py`	TaskCompleted	Record subagent completion metadata
`subagent-completion-guard.py`	SubagentStop	Block main-branch commits, enforce read-only reviewers
`session-learning-recorder.py`	Stop	Warn on sessions with no learnings
`session-summary.py`	Stop	Persist session metrics to learning.db

Sync Lifecycle

hooks/sync-to-user-claude.py fires on SessionStart when cwd is this repo. It copies the repo into ~/.claude/ so that Claude Code instances in other repos get access to agents, skills, hooks, and scripts.

What gets synced:

Source	Destination	Sync Mode
`agents/`	`~/.claude/agents/`	File-by-file copy, stale files removed
`skills/`	`~/.claude/skills/`	File-by-file copy, stale files removed
`hooks/`	`~/.claude/hooks/`	File-by-file copy, stale files removed
`scripts/`	`~/.claude/scripts/`	File-by-file copy, stale files removed
`commands/`	`~/.claude/commands/`	Additive only (never removes)
`CLAUDE-soul-template.md`	`~/.claude/CLAUDE.md`	Overwrite with backup (max 3 backups)
`.claude/settings.json` hooks	`~/.claude/settings.json` hooks	Replace hook section entirely
`.mcp.json`	`~/.mcp.json`	Merge servers (don't overwrite existing)

Unchanged files are skipped via content comparison.

Settings Architecture

File	Location	Tracked?	Purpose
`settings.json`	`~/.claude/settings.json`	No (runtime)	Hook registrations, permissions. Repo hooks replace on sync.
`settings.local.json`	`.claude/settings.local.json`	No (gitignored)	Repo-local overrides (e.g. MCP tool permissions)
`CLAUDE.md`	`~/.claude/CLAUDE.md`	No (synced from template)	Soul document -- global instructions for all sessions
`CLAUDE-soul-template.md`	Repo root	Yes	Source of truth for CLAUDE.md

The .claude/ directory inside the repo is gitignored. Only settings.local.json lives there. The ~/.claude/ directory is the runtime home -- hooks, agents, skills all resolve from there when working in external repos.

Key Files

Path	Purpose
`CLAUDE-soul-template.md`	Soul document template, synced to `~/.claude/CLAUDE.md`
`agents/INDEX.json`	Auto-generated agent registry (triggers, pairs_with, complexity)
`skills/INDEX.json`	Auto-generated skill registry
`install.sh`	One-shot installer: `--symlink` or `--copy` to `~/.claude/`
`scripts/learning-db.py`	CLI for learning.db: learn, record, query, stats, graduate, prune
`scripts/generate-agent-index.py`	Regenerates `agents/INDEX.json` from agent frontmatter
`scripts/generate-skill-index.py`	Regenerates `skills/INDEX.json` from skill frontmatter
`scripts/classify-repo.py`	Classifies repos as protected-org or standard
`scripts/scan-ai-patterns.py`	Scans docs for AI writing patterns against `scripts/data/banned-patterns.json`
`scripts/feature-state.py`	Feature lifecycle state machine (`.feature/` directory)
`scripts/adr-query.py`	ADR session management: register, query, check compliance
`scripts/score-component.py`	Deterministic health scorer for agents and skills (9 checks, 100-point rubric)
`scripts/lockfile.py`	PID-based concurrent access protection (acquire, release, status)
`scripts/manifest.py`	Snapshot/undo/verify for system upgrades with SHA-256 checksums
`scripts/task-status.py`	Pipeline progress tracking (start, update, done, show, clear)
`hooks/lib/learning_db_v2.py`	Core learning database module -- all hooks import from here
`hooks/lib/hook_utils.py`	Shared hook utilities: JSON output, fallbacks, frontmatter parsing
`hooks/lib/quality_gate.py`	Quality gate enforcement helpers
`AGENT_TEMPLATE_V2.md`	Template for creating new agents
`skills/shared-patterns/`	Shared anti-rationalization, gate enforcement, verification patterns

Learning System

Database: ~/.claude/learning/learning.db (SQLite, WAL mode, FTS5 full-text search)

Schema (core table)

CREATE TABLE learnings (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    topic TEXT NOT NULL,
    key TEXT NOT NULL,
    value TEXT NOT NULL,
    category TEXT NOT NULL,        -- error|pivot|review|design|debug|gotcha|effectiveness
    confidence REAL DEFAULT 0.5,
    tags TEXT,
    source TEXT NOT NULL,
    source_detail TEXT,
    project_path TEXT,
    session_id TEXT,
    observation_count INTEGER DEFAULT 1,
    success_count INTEGER DEFAULT 0,
    failure_count INTEGER DEFAULT 0,
    first_seen TEXT,
    last_seen TEXT,
    graduated_to TEXT,             -- target file when promoted to agent/skill
    error_signature TEXT,
    error_type TEXT,
    fix_type TEXT,                 -- auto|manual|skill
    fix_action TEXT,
    UNIQUE(topic, key)
);

FTS5 virtual table learnings_fts indexes topic, key, value, tags for fast keyword search.

CLI

# Record a learning scoped to a skill
python3 scripts/learning-db.py learn --skill go-testing "table tests need t.Parallel()"

# Record scoped to an agent
python3 scripts/learning-db.py learn --agent golang-general-engineer "always check go.sum"

# Query learnings
python3 scripts/learning-db.py query --topic debugging --min-confidence 0.6

# Stats
python3 scripts/learning-db.py stats

# Graduate a learning into an agent or skill file
python3 scripts/learning-db.py graduate TOPIC KEY TARGET

# Prune low-confidence old entries
python3 scripts/learning-db.py prune --below-confidence 0.3 --older-than 90

# ROI report — cohort comparison of sessions with/without retro knowledge
python3 scripts/learning-db.py roi [--json]

# Show stale entries (low confidence, old, not graduated)
python3 scripts/learning-db.py stale [--min-age-days 30]

# Archive stale entries
python3 scripts/learning-db.py stale-prune --dry-run
python3 scripts/learning-db.py stale-prune --confirm

Lifecycle

Record: hooks capture errors, review findings, session patterns automatically
Boost/Decay: confidence adjusts -- success boosts, failure decays, inactivity decays
Inject: retro-knowledge-injector.py queries FTS5 on every UserPromptSubmit, injects relevant entries above confidence threshold
Graduate: high-confidence entries get promoted into agent/skill files via learning-db.py graduate

Frontmatter Schema

Agent Frontmatter

---
name: {domain}-{function}-engineer       # kebab-case, ends with -engineer
version: 2.0.0
description: |
  Use this agent when [trigger conditions].
color: blue | green | orange | red | purple
hooks:
  PostToolUse:
    - type: command
      command: "python3 -c \"...\""
      timeout: 3000
routing:
  triggers:
    - keyword1
    - keyword2
  pairs_with:
    - related-skill
  complexity: Simple | Medium | Medium-Complex | Complex
  category: language | infrastructure | review | meta
---

Skill Frontmatter

---
name: skill-name                          # kebab-case
description: |
  What this skill does and when to use it.
version: 1.0.0
user-invocable: true | false              # true = appears in /slash menu
context: fork                             # optional: run in isolated sub-agent
agent: golang-general-engineer            # optional: declare executor agent
model: opus | sonnet | haiku              # optional: model preference
allowed-tools:
  - Read
  - Write
  - Bash
  - Grep
  - Glob
  - Edit
  - Skill
  - Task
  - Agent
routing:
  triggers:
    - keyword1
  pairs_with:
    - related-skill
  complexity: Simple | Medium | Complex
  category: process | content | pipeline | validation
---

Key difference: user-invocable: true makes a skill appear in the slash command menu. Most skills are false -- they're invoked by the router, not directly by users.

Force-Route Triggers

These are mandatory. When triggers match, the skill fires before any other routing.

Skill	Triggers
`go-testing`	Go test, *_test.go, table-driven, t.Run, t.Helper, benchmark, mock
`go-concurrency`	goroutine, channel, sync.Mutex, WaitGroup, worker pool, fan-out, rate limit
`go-error-handling`	error handling, fmt.Errorf, errors.Is, errors.As, %w, sentinel error
`go-code-review`	review Go, Go PR, Go code review, check Go quality
`go-anti-patterns`	anti-pattern, code smell, over-engineering, premature abstraction
`go-sapcc-conventions`	sapcc, sap-cloud-infrastructure, go-bits, keppel, go-api-declarations
`python-quality-gate`	bandit, Python security scan, Python SAST
`create-voice`	create voice, new voice, build voice, voice from samples, calibrate voice
`voice-orchestrator`	write in voice, generate voice content, voice workflow
`feature-design`	design feature, feature design, think through feature
`feature-plan`	plan feature, feature plan, break down design
`feature-implement`	implement feature, execute plan, start building
`feature-validate`	validate feature, run quality gates
`feature-release`	release feature, merge feature, ship it
`system-upgrade`	upgrade agents, system upgrade, claude update, upgrade skills
`de-ai-pipeline`	de-ai docs, clean ai patterns, fix ai writing, scan and fix docs
`pr-sync`	push, push this, commit and push, create a PR, create PR, open PR
`git-commit-flow`	commit, commit this, commit changes, stage and commit
`github-actions-check`	check CI, CI status, actions status, did CI pass
`install`	install toolkit, verify installation, health check toolkit

Pipeline Registry

Pipeline skills have explicit phases with gates between them.

Pipeline Skill	Phases
`system-upgrade`	CHANGELOG -> AUDIT -> PLAN -> IMPLEMENT -> VALIDATE -> DEPLOY
`skill-creation-pipeline`	DISCOVER -> DESIGN -> SCAFFOLD -> VALIDATE -> INTEGRATE
`hook-development-pipeline`	SPEC -> IMPLEMENT -> TEST -> REGISTER -> DOCUMENT
`research-pipeline`	SCOPE -> GATHER -> SYNTHESIZE -> VALIDATE -> DELIVER
`agent-upgrade`	AUDIT -> DIFF -> PLAN -> IMPLEMENT -> RE-EVALUATE
`explore-pipeline`	SCAN -> MAP -> ANALYZE -> REPORT
`research-to-article`	RESEARCH -> COMPILE -> GROUND -> GENERATE -> VALIDATE -> REFINE -> OUTPUT
`pr-pipeline`	CLASSIFY -> STAGE -> REVIEW -> COMMIT -> PUSH -> CREATE -> VERIFY -> CLEANUP
`voice-orchestrator`	LOAD -> GROUND -> GENERATE -> VALIDATE -> REFINE -> OUTPUT -> CLEANUP
`github-profile-rules`	PROFILE-SCAN -> CODE-ANALYSIS -> REVIEW-MINING -> PATTERN-SYNTHESIS -> RULES-GENERATION -> VALIDATION -> OUTPUT
`doc-pipeline`	RESEARCH -> OUTLINE -> GENERATE -> VERIFY -> OUTPUT
`workflow-orchestrator`	BRAINSTORM -> WRITE-PLAN -> EXECUTE-PLAN
`de-ai-pipeline`	SCAN -> FIX -> VERIFY (loop max 3) -> REPORT

Anti-AI Writing System

The toolkit includes deterministic tooling for detecting and removing AI writing patterns.

Components

Component	Type	What It Does
`scripts/scan-ai-patterns.py`	Script	Regex scan against `scripts/data/banned-patterns.json` (323 patterns, 24 categories)
`skills/anti-ai-editor/`	Skill	Targeted revision: scan for patterns, propose minimal fixes, preserve meaning
`pipelines/de-ai-pipeline/`	Skill	Full loop: SCAN -> FIX -> VERIFY, max 3 iterations
`scripts/voice_analyzer.py`	Script	Extract metrics from writing samples
`scripts/voice_validator.py`	Script	Validate content against voice profiles

Wabi-Sabi Principle

Natural imperfections are features. Sterile grammatical perfection is an AI tell.

Do: sentence fragments, run-on sentences, contractions, dashes instead of semicolons, varied sentence length, thoughts that trail off

Don't: "delve", "leverage", "comprehensive", "robust", "streamline", "empower", "harness", "foster", "spearheaded", "synergy"

Scan Command

python3 scripts/scan-ai-patterns.py                      # scan all docs
python3 scripts/scan-ai-patterns.py docs/some-file.md    # scan one file
python3 scripts/scan-ai-patterns.py --errors-only         # suppress warnings
python3 scripts/scan-ai-patterns.py --json                # machine-readable

Exit 0 = clean. Exit 1 = patterns found.

Agent Categories

Category	Examples
Language	golang-general-engineer, python-general-engineer, typescript-frontend-engineer, nodejs-api-engineer
Infrastructure	kubernetes-helm-engineer, ansible-automation-engineer, prometheus-grafana-engineer, rabbitmq-messaging-engineer
Review	reviewer-security, reviewer-business-logic, reviewer-performance, reviewer-concurrency, reviewer-dead-code
Data	database-engineer, sqlite-peewee-engineer, data-engineer
Content	technical-documentation-engineer, technical-journalist-writer
Meta	skill-creator, system-upgrade-engineer, pipeline-orchestrator-engineer, research-coordinator-engineer
Perses	perses-core-engineer, perses-dashboard-engineer, perses-operator-engineer, perses-plugin-engineer
UI/Perf	ui-design-engineer, performance-optimization-engineer, react-portfolio-engineer
Research	research-coordinator-engineer, research-subagent-executor

MCP Integrations

MCP Server	Auto-Use Triggers	Tools
gopls	Go workspace, .go files, go.mod	`go_workspace`, `go_file_context`, `go_diagnostics`, `go_symbol_references`, `go_package_api`, `go_vulncheck`
Context7	Library docs, API reference, "how do I use X"	`resolve-library-id`, `query-docs`
Playwright	Automated browser validation, screenshot tests	`browser_navigate`, `browser_snapshot`, `browser_take_screenshot`, etc.
Chrome DevTools	Live browser debugging, lighthouse audits	`list_pages`, `navigate_page`, `take_screenshot`, `lighthouse_audit`

MCP instructions are injected into the main session only. Subagents must use ToolSearch() to discover deferred MCP tools.

Quick Reference: Routing a Request

User says "fix the failing Go tests"

1. /do classifies: Simple (code change)
2. Force-route check: "Go test" matches -> go-testing (MANDATORY)
3. Agent: golang-general-engineer
4. Skill: go-testing (force-routed)
5. Enhancements: anti-rationalization-testing auto-injected
6. Plan: task_plan.md created (Simple+ complexity)
7. Dispatch: agent executes with go-testing methodology
8. Learn: record outcome to learning.db

Provide feedback

Saved searches

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Claude Code Toolkit — AI Agent Reference

Repository Map

Component Inventory

Commands

Architecture

Entry Point: `/do`

Hook System

Event Types

Hook Output Format

Hook-to-Event Mapping

Sync Lifecycle

Settings Architecture

Key Files

Learning System

Schema (core table)

CLI

Lifecycle

Frontmatter Schema

Agent Frontmatter

Skill Frontmatter

Force-Route Triggers

Pipeline Registry

Anti-AI Writing System

Components

Wabi-Sabi Principle

Scan Command

Agent Categories

MCP Integrations

Quick Reference: Routing a Request

FilesExpand file tree

for-claude-code.md

Latest commit

History

for-claude-code.md

File metadata and controls

Claude Code Toolkit — AI Agent Reference

Repository Map

Component Inventory

Commands

Architecture

Entry Point: /do

Hook System

Event Types

Hook Output Format

Hook-to-Event Mapping

Sync Lifecycle

Settings Architecture

Key Files

Learning System

Schema (core table)

CLI

Lifecycle

Frontmatter Schema

Agent Frontmatter

Skill Frontmatter

Force-Route Triggers

Pipeline Registry

Anti-AI Writing System

Components

Wabi-Sabi Principle

Scan Command

Agent Categories

MCP Integrations

Quick Reference: Routing a Request

Entry Point: `/do`