Imported from MikeCheng1208/BattleTree (.agents/skills/docs-management/SKILL.md). Install upstream with npx skills add MikeCheng1208/BattleTree --skill docs-management. Copyright stays with the author.

Claude Docs Management

🚨🚨🚨 MANDATORY: Hybrid Parallel Pattern 🚨🚨🚨

STOP - Before using this skill for ANY Claude Code documentation query:

IF YOU ARE THE MAIN AGENT, you MUST invoke BOTH sources in the same message:

1. This skill (docs-management) - local cache, token-efficient
2. claude-code-guide subagent - live web search

[Skill tool: docs-management]
"Find documentation about {topic}"

[Task tool: claude-code-guide] (SAME MESSAGE - USE THIS EXACT PROMPT)
"First WebFetch https://code.claude.com/docs/en/claude_code_docs_map.md to find
relevant doc pages about {topic}. Then WebFetch those specific pages. Use WebSearch
only if needed for additional context. Do NOT use Skill tool (not available).
Return key findings with source URLs."

⚠️ CRITICAL: claude-code-guide does NOT have Skill tool access. Always prompt it to use WebSearch/WebFetch explicitly. If you see "No such tool: Skill" error, you prompted it wrong.

This is AUTOMATIC. Do NOT wait for user to ask for it.

IF YOU ARE A SUBAGENT: Note in your response that main agent should also query claude-code-guide.

🚨 CRITICAL: Path Doubling Prevention - MANDATORY

ABSOLUTE PROHIBITION: NEVER use cd with && in PowerShell when running scripts from this skill.

The Problem: If your current working directory is already inside the skill directory, using relative paths causes PowerShell to resolve paths relative to the current directory instead of the repository root, resulting in path doubling.

REQUIRED Solutions (choose one):

1. ✅ ALWAYS use helper scripts (recommended - they handle path resolution automatically)
2. ✅ Use absolute path resolution (if not using helper script)
3. ✅ Use separate commands (never cd with &&)

NEVER DO THIS:

• ❌ Chain cd with &&: cd <relative-path> && python <script> causes path doubling
• ❌ Assume current directory
• ❌ Use relative paths when current dir is inside skill directory

For all scripts: Always run from repository root using relative paths, OR use helper scripts that handle path resolution automatically.

🚨 CRITICAL: Large File Handling - MANDATORY SCRIPT USAGE

⚠️ ABSOLUTE PROHIBITION: NEVER use read_file tool on the index.yaml file

The file exceeds 25,000 tokens and will ALWAYS fail. You MUST use scripts.

✅ REQUIRED: ALWAYS use manage_index.py scripts for ANY index.yaml access:

python scripts/management/manage_index.py count
python scripts/management/manage_index.py list
python scripts/management/manage_index.py get <doc_id>
python scripts/management/manage_index.py verify

All scripts automatically handle large files via index_manager.py.

Available Slash Commands

Use the consolidated docs-ops skill for common workflows:

• /claude-ecosystem:docs-ops scrape - Scrape all configured Claude documentation sources, then refresh index and validate
• /claude-ecosystem:docs-ops refresh - Refresh the local index and metadata without scraping from remote sources
• /claude-ecosystem:docs-ops validate - Validate the index and references for consistency and drift without scraping
• /claude-ecosystem:docs-ops rebuild-index - Force rebuild the search index from filesystem
• /claude-ecosystem:docs-ops clear-cache - Clear the documentation search cache

Overview

This skill provides automation tooling for documentation management. It manages:

• Canonical storage (encapsulated in skill) - Single source of truth for official docs
• Subsection extraction - Token-optimized extracts for skills (60-90% savings)
• Drift detection - Hash-based validation against upstream sources
• Sync workflows - Quarterly maintenance automation
• Documentation discovery - Keyword-based search and doc_id resolution
• Index management - Metadata, keywords, tags, aliases for resilient references

Core value: Prevents link rot, enables offline access, optimizes token costs, automates maintenance, and provides resilient doc_id-based references.

Quick Reference: Which Command to Use

Key Workflow: search by keywords → Get doc_id from results → content by doc_id

Important distinctions:

• search and query accept flexible keywords (no full doc_id needed)
• content, resolve, and related require full doc_id (e.g., code-claude-com-docs-en-skills)

When to Use This Skill

This skill should be used when:

• Scraping documentation - Fetching docs from sitemaps or docs maps
• Finding documentation - Searching for docs by keywords, category, or natural language
• Resolving doc references - Converting doc_id to file paths
• Managing index metadata - Adding keywords, tags, aliases, updating metadata
• Rebuilding index - Regenerating index from filesystem (handles renames/moves)

Hybrid Parallel Documentation Strategy

CRITICAL: This section is the authoritative source for Claude Code documentation access patterns.

Architecture Constraint

Skills cannot spawn subagents. Only the main conversation thread can use the Task tool.

This means:

• When main agent loads this skill → Main agent must also invoke claude-code-guide in parallel
• When subagent loads this skill → Subagent should note in response that main agent should invoke claude-code-guide for live coverage
• When command invokes this skill → Same as main agent (commands run in main context)

Caller-Aware Guidance

If you are the main agent:

• You MUST invoke both this skill AND claude-code-guide subagent in the SAME message
• This is the only way to get comprehensive Claude Code documentation coverage

If you are a subagent:

• You CANNOT invoke claude-code-guide yourself (architectural constraint)
• Include in your response: "For comprehensive coverage, main agent should also query claude-code-guide subagent"
• Proceed with local cache results

Always-Parallel Pattern (Main Agent Only)

⚠️ MANDATORY DEFAULT BEHAVIOR - NOT OPTIONAL:

When ANY Claude Code documentation query is detected, the main agent MUST automatically:

1. Invoke docs-management skill (local cache)
2. Spawn claude-code-guide subagent (live web) in the same message

This is automatic. The user does NOT need to ask for it.

Detection Triggers

Use both sources automatically when user asks about:

• Claude Code features (hooks, skills, memory, MCP, plugins, settings, etc.)
• How to do something in Claude Code
• Claude Code configuration or troubleshooting
• Any topic in the Claude Code documentation

Same-Message Parallel Invocation

# Main agent sends BOTH in a single message (AUTOMATIC):

[Skill tool: docs-management]
"Find documentation about {topic}"

[Task tool: claude-code-guide] (same message = parallel execution)
"First WebFetch https://code.claude.com/docs/en/claude_code_docs_map.md to find
relevant doc pages about {topic}. Then WebFetch those specific pages. Use WebSearch
only if needed for additional context. Do NOT use Skill tool (not available).
Return key findings with source URLs."

IMPORTANT: claude-code-guide is a built-in subagent with tools: Glob, Grep, Read, WebFetch, WebSearch. It does NOT have the Skill tool - it's designed for web search, not local skill invocation. Always prompt it to use WebSearch/WebFetch explicitly.

Synthesis Step

After both complete:

• Combine results from both sources
• Local cache provides category context and token efficiency
• Live search provides currency and gap-filling
• Note any discrepancies between sources

Two Documentation Sources

Fallback Behavior

• Plugin not installed: Use claude-code-guide only
• Live search unavailable: This skill provides complete local cache
• Both sources disagree: Flag discrepancy, prefer official docs, investigate

Automatic Behavior Summary

There is no manual trigger. This is default behavior for Claude Code documentation queries.

Three-Source Troubleshooting Pattern

When troubleshooting errors, bugs, or unexpected behavior, use three sources in parallel:

Troubleshooting triggers (automatically detected by hook):

• "error", "bug", "broken", "not working", "fails", "crash"
• "debug", "troubleshoot", "workaround", "issue", "problem"
• "doesn't work", "won't work", "can't", "isn't firing"

Example prompt for claude-code-issue-researcher:

Search GitHub issues in anthropics/claude-code for: [ERROR/PROBLEM DESCRIPTION].
Check both open and closed issues. Report issue numbers, status, and any workarounds.

Correct Subagent Pattern

When spawning docs-researcher (or any subagent that uses this skill), the main agent should ALSO spawn claude-code-guide in the same message for comprehensive coverage:

# Main agent spawns BOTH in a single message:

[Task tool: docs-researcher subagent]
"Research Claude Code memory/CLAUDE.md files"

[Task tool: claude-code-guide subagent] (same message = parallel)
"Use WebSearch to find current Claude Code documentation about memory and
CLAUDE.md files on code.claude.com. Return key findings with URLs."

# After both complete, synthesize results

Why both? The docs-researcher uses local cache (fast, token-efficient), while claude-code-guide searches live web (always current). Together they provide comprehensive coverage.

Hierarchical Categories (from docs_map.md)

The index includes category hierarchy from the official Claude Code docs map:

Categories are stored in doc_map_category field. Query by category:

resolver.get_by_category("Build with Claude Code")  # Returns all docs in category
resolver.list_categories()  # Returns all categories with counts

Category Enrichment

After scraping, update categories from the official docs map:

python scripts/core/enrich_categories.py           # Update categories
python scripts/core/enrich_categories.py --dry-run # Preview changes

Workflow Execution Pattern

CRITICAL: This section defines HOW to execute operations in this skill.

Delegation Strategy

Default approach: Delegate to Task agent

For ALL scraping, validation, and index operations, delegate execution to a general-purpose Task agent.

How to invoke:

Use the Task tool with:

• subagent_type: "general-purpose"
• description: Short 3-5 word description
• prompt: Full task description with execution instructions

Execution Pattern

Scripts run in FOREGROUND by default. Do NOT background them.

When Task agents execute scripts:

• ✅ Run directly: python .claude/skills/docs-management/scripts/core/scrape_all_sources.py --parallel --skip-existing
• ✅ Streaming logs: Scripts emit progress naturally via stdout
• ✅ Wait for completion: Scripts exit when done with exit code
• ❌ NEVER use run_in_background=true: Scripts are designed for foreground execution
• ❌ NEVER poll output: Streaming logs appear automatically, no BashOutput polling needed
• ❌ NEVER use background jobs: No &, no nohup, no background process management

Anti-Pattern Detection

Red flags indicating incorrect execution:

🚩 Using run_in_background=true in Bash tool 🚩 Repeated BashOutput calls in a loop 🚩 Checking process status with ps or pgrep 🚩 Manual polling of script output 🚩 Background job management (&, nohup, jobs) 🚩 Using BashOutput AFTER Task agent completes ← CRITICAL RED FLAG

If you recognize these patterns, STOP and correct immediately.

After Task Agent Completes

CRITICAL: When the Task agent reports "Done", READ its report and summarize to the user. DO NOT use BashOutput.

Correct workflow:

1. Task agent reports "Done (X tool uses · Y tokens · Z time)"
2. ✅ READ the agent's message containing its final report
3. ✅ SUMMARIZE the agent's findings to the user
4. ❌ NEVER use BashOutput to "check the real results"
5. ❌ NEVER poll or verify what the agent already reported

Error and Warning Reporting

CRITICAL: Report ALL errors, warnings, and issues - never suppress or ignore them.

When executing scripts via Task agents:

• ✅ Report script errors: Exit codes, exceptions, error messages
• ✅ Report warnings: Deprecation warnings, import issues, configuration problems
• ✅ Report unexpected output: 404s, timeouts, validation failures
• ✅ Include context: What was being executed when the error occurred

Red flags that indicate issues:

🚩 Non-zero exit code 🚩 Lines containing "ERROR", "FAILED", "Exception", "Traceback" 🚩 "WARNING" or "WARN" messages 🚩 "404 Not Found", "500 Internal Server Error"

Domain-Specific Reporting for Scraping

CRITICAL: When reporting scraping results, distinguish behavior by domain.

Domain-Specific .md URL Behavior:

1. docs.claude.com and code.claude.com: These domains serve .md URLs successfully
2. anthropic.com: These domains do NOT serve .md URLs (404 expected, configured with try_markdown: false)

Accurate Reporting:

✅ Good (Domain-Specific): "docs.claude.com: 97 URLs using direct .md (97 skipped/unchanged). anthropic.com: 164 URLs using HTML conversion (158 skipped/unchanged)."

❌ Bad (Misleading): "All .md URL attempts returned 404 (expected - these are HTML pages)" ← This is misleading because Claude domains successfully use .md URLs

Quick Start

Refresh Index End-to-End (No Scraping)

Use this when you want to rebuild and validate the local index/metadata without scraping:

⚠️ IMPORTANT: Use Python 3.13 for validation - spaCy/Pydantic have compatibility issues with Python 3.14+

# Use Python 3.13 for full compatibility with spaCy
py -3.13 .claude/skills/docs-management/scripts/management/refresh_index.py

Optional flags:

# Check for missing files before rebuilding
py -3.13 .claude/skills/docs-management/scripts/management/refresh_index.py --check-missing-files

# Detect drift (404s, missing files) after rebuilding
py -3.13 .claude/skills/docs-management/scripts/management/refresh_index.py --check-drift

# Detect and automatically cleanup drift
py -3.13 .claude/skills/docs-management/scripts/management/refresh_index.py --check-drift --cleanup-drift

This script runs the full pipeline:

• ✅ Checks dependencies
• ✅ (Optional) Checks for missing files
• ✅ Rebuilds the index from the filesystem
• ✅ Extracts keywords & metadata for all documents
• ✅ Validates metadata coverage
• ✅ Generates a summary report
• ✅ (Optional) Detects and cleans up drift

Expected runtime: ~20-30 seconds for ~500 documents

Scrape All Sources (Used by /scrape-official-docs)

Use this when the user explicitly wants to hit the network and scrape docs:

Python Version Requirement

• Python 3.14 works by default for scraping
• Python 3.13 required for spaCy operations (keyword extraction, metadata extraction)

# Step 1: Scrape documentation (Python 3.14+ works)
python .claude/skills/docs-management/scripts/core/scrape_all_sources.py \
  --parallel \
  --skip-existing

# Step 2: IMMEDIATELY run validation after scraping completes
# ⚠️ Use Python 3.13 for validation (spaCy compatibility)
py -3.13 .claude/skills/docs-management/scripts/management/refresh_index.py

# Step 3: Clean up aged-out Anthropic articles (reads max_age from sources.json)
python .claude/skills/docs-management/scripts/maintenance/cleanup_old_anthropic_docs.py --execute

Validation and Cleanup Are Required After Scraping

Since --auto-validate is now default: False (for speed), you MUST run validation and cleanup separately immediately after scraping.

Optional: Detect and cleanup drift after scraping:

# Auto-cleanup workflow (detect and cleanup in one flag)
python .claude/skills/docs-management/scripts/core/scrape_all_sources.py \
  --parallel \
  --skip-existing \
  --auto-cleanup

# Then validate (use Python 3.13)
py -3.13 .claude/skills/docs-management/scripts/management/refresh_index.py

Find Documentation

⚠️ CRITICAL: Global flags MUST come BEFORE the subcommand:

# ✅ CORRECT - global flags before subcommand
python find_docs.py --json --limit 10 search skills frontmatter

# ❌ WRONG - global flags after subcommand (will fail with "unrecognized arguments")
python find_docs.py search skills frontmatter --json

Examples:

# Resolve doc_id to file path
python .claude/skills/docs-management/scripts/core/find_docs.py resolve <doc_id>

# Search by keywords (default: 25 results)
python .claude/skills/docs-management/scripts/core/find_docs.py search skills progressive-disclosure

# Search with custom limit (global options come before subcommand)
python .claude/skills/docs-management/scripts/core/find_docs.py --limit 10 search skills

# Search without limit (returns all matching results)
python .claude/skills/docs-management/scripts/core/find_docs.py --no-limit search skills

# Search with minimum score threshold (filters low-relevance results)
python .claude/skills/docs-management/scripts/core/find_docs.py --min-score 20 search skills

# Natural language search
python .claude/skills/docs-management/scripts/core/find_docs.py query "how to create skills"

# List by category
python .claude/skills/docs-management/scripts/core/find_docs.py category api

# List by tag
python .claude/skills/docs-management/scripts/core/find_docs.py tag skills

Search Accepts Flexible Keywords (no full doc_ids needed):

• Single keyword: search skills
• Multiple keywords: search skills progressive disclosure
• Partial words work via token matching: search skill matches "skills"
• Singular/plural auto-handled: "skill" matches "skills"
• Stop words removed automatically from queries: "how", "to", "the", etc.

Search Options:

When results are truncated, output shows "showing X of Y total" to indicate more results are available.

Hybrid Search (Default Behavior)

By default, search performs both index and content search:

1. Index search - Fast keyword matching against document metadata (title, description, keywords, tags)
2. Content search - Grep through actual file contents for matches not in index

Result markers:

• [SUBSECTION] - Match found in a specific document section (click to extract)
• [CONTENT] - Match found in file content (not in metadata index)
• No marker - Standard index match

Performance options:

• Use --fast for index-only search (faster, but may miss content-only matches)
• Use --separate to display index and content matches in separate sections

Search Scoring

Results are ranked by a multi-factor scoring system:

• Title matches (highest weight, 14 points)
• Description matches (10 points)
• Keyword field matches (8-10 points, with variant detection)
• Tag matches (5-7 points)
• Coverage multipliers (1.5-2.0x for multi-term matches)
• Domain weighting (Claude Code docs prioritized over general Anthropic docs)

Use --verbose to see scores for debugging relevance issues.

find_docs.py Command Reference

Related Documents Example:

# Find documents related to skills documentation
python .claude/skills/docs-management/scripts/core/find_docs.py related code-claude-com-docs-en-skills

# Limit results
python .claude/skills/docs-management/scripts/core/find_docs.py --limit 5 related code-claude-com-docs-en-skills

Related documents are scored by shared tags (3x weight) and shared keywords (2x weight).

Subsection Extraction (Token-Optimized)

To extract a specific section from a document (60-90% token savings):

Option 1: Using find_docs.py content command:

python scripts/core/find_docs.py content code-claude-com-docs-en-skills --section "Available metadata fields"

Option 2: Using get_subsection_content.py (dedicated script):

python scripts/core/get_subsection_content.py code-claude-com-docs-en-skills \
  --section "Available metadata fields"

Discover Available Sections (--list-sections):

# List all sections in a document
python scripts/core/get_subsection_content.py code-claude-com-docs-en-skills --list-sections

# Output shows hierarchical structure with heading levels
#   # Agent Skills
#     ## Create your first Skill
#     ## How Skills work
#       ### Where Skills live

Fuzzy Section Matching:

Section names support fuzzy matching - partial or word-overlap matches work:

# Exact: "Available metadata fields"
# Fuzzy: "metadata fields" -> matches "Available metadata fields"
# Fuzzy: "tool access" -> matches "Restrict tool access with allowed-tools"

python scripts/core/get_subsection_content.py code-claude-com-docs-en-skills   --section "metadata fields"
# Output: Fuzzy match: 'metadata fields' -> 'Available metadata fields'

Note: The resolve command ONLY returns file paths. Use content to get actual document content with optional section extraction.

Configuration System

The docs-management skill uses a unified configuration system with a single source of truth.

Configuration Files:

• config/defaults.yaml - Central configuration file with all default values
• config/config_registry.py - Canonical configuration system with environment variable support
• references/sources.json - Documentation sources configuration (required for scraping)

Path Configuration:

All paths configured in config/defaults.yaml under the paths section.

Environment Variable Overrides:

All configuration values can be overridden using environment variables: CLAUDE_DOCS_<SECTION>_<KEY>

Full details: references/technical-details.md#configuration

Dependencies & Environment

Required: pyyaml, requests, beautifulsoup4, markdownify Optional (recommended): spacy, yake (for enhanced keyword extraction)

Quick setup:

python .claude/skills/docs-management/scripts/setup/setup_dependencies.py --install-required

Auto-installation: The extract-keywords command automatically installs optional dependencies if missing.

Full details: references/technical-details.md#dependencies

Core Capabilities

1. Scraping Documentation

Fetch documentation from official sources and store in canonical storage. Features: sitemap/docs map parsing, HTML→Markdown conversion, direct .md URL fetching (30-40% token savings), automatic metadata tracking, domain-based folder organization.

Guide: references/capabilities/scraping-guide.md

2. Extracting Subsections (Internal Use)

Extract specific markdown sections for internal skill operations. Features: ATX-style heading structure parsing, section boundaries detection, provenance frontmatter, token economics (60-90% savings typical).

Guide: references/capabilities/extraction-guide.md

3. Change Detection

Detect new and removed documentation pages from sitemaps, and detect content changes via hash comparison. Features: new/removed page detection, content hash comparison, automatic stale marking, change reporting and audit logs.

Guide: references/capabilities/change-detection-guide.md

4. Finding and Resolving Documentation

Discover and resolve documentation references using doc_id, keywords, or natural language queries. Features: doc_id resolution, keyword-based search, natural language query processing, subsection discovery and extraction, category and tag filtering, alias resolution.

5. Index Management and Maintenance

Maintain index metadata, keywords, tags, and rebuild index from filesystem. Scripts: manage_index.py, rebuild_index.py, generate_report.py, verify_index.py.

6. Age-Based Cleanup

Remove documentation that has aged out based on published_at dates. Anthropic sources (engineering, news, research) have a max_age_days threshold configured in references/sources.json. Articles older than this threshold are skipped during scraping; this cleanup removes any previously-scraped articles that have since aged out.

# Clean up aged-out Anthropic articles (dry-run by default)
# Reads max_age_days from sources.json automatically
python scripts/maintenance/cleanup_old_anthropic_docs.py

# Execute cleanup (actually delete files)
python scripts/maintenance/cleanup_old_anthropic_docs.py --execute

# Override with custom age threshold if needed
python scripts/maintenance/cleanup_old_anthropic_docs.py --max-age 90 --execute

This should be run after scraping and validation to ensure the canonical directory stays clean.

Workflows

Common maintenance and operational workflows for documentation management:

• Adding New Documentation Source - Onboarding new docs from sitemaps or docs maps
• Scraping Multiple Sources - Validation checkpoints to prevent wasted time/tokens
• Token-Optimized Subsection Retrieval - Workflow for extracting subsections instead of full documents

Detailed Workflows: references/workflows.md

Metadata & Keyword Audit Workflows

Lightweight audit:

py -3.13 .claude/skills/docs-management/scripts/validation/validate_index_vs_docs.py --summary-only

Tag configuration audit:

py -3.13 .claude/skills/docs-management/scripts/validation/audit_tag_config.py --summary-only

Full details: references/workflows.md#metadata--keyword-audit

Platform-Specific Requirements

Windows Users

MUST use PowerShell (recommended) or prefix Git Bash commands with MSYS_NO_PATHCONV=1

Git Bash on Windows converts Unix paths to Windows paths, breaking filter patterns.

See: Troubleshooting Guide

Troubleshooting

spaCy Installation Issues

Problem: spaCy installation fails with Python 3.14+.

Solution: The script automatically detects and uses Python 3.13 if available. No manual intervention needed!

If Python 3.13 not available: Install Python 3.13:

• Windows: winget install --id Python.Python.3.13 -e --source winget
• macOS: brew install python@3.13
• Linux: sudo apt install python3.13

Full troubleshooting: references/troubleshooting.md

Public API

The docs-management skill provides a clean public API for external tools:

from official_docs_api import (
    find_document,
    resolve_doc_id,
    get_docs_by_tag,
    get_docs_by_category,
    search_by_keywords,
    detect_drift,
    cleanup_drift,
    refresh_index
)

Full API documentation: See Public API section in original SKILL.md

Plugin Maintenance

For plugin-specific maintenance workflows (versioning, publishing updates, changelog):

See: references/plugin-maintenance.md

Quick reference:

• Update workflow: Scrape → Validate → Review → Commit → Version bump → Push
• Version bumps: Patch for doc refresh, Minor for new sources/features, Major for breaking changes
• Testing: Run manage_index.py verify and test search before pushing

Development Mode

When developing this plugin locally, you may want changes to go to your dev repo instead of the installed plugin location. This skill supports explicit dev/prod mode separation via environment variable.

How It Works

By default, scripts write to wherever the plugin is installed (typically ~/.claude/plugins/marketplaces/...). When OFFICIAL_DOCS_DEV_ROOT is set to a valid skill directory, all paths resolve to that location instead.

Enabling Dev Mode

One-time setup:

# Navigate to your dev repo skill directory
cd /path/to/your/claude-code-plugins/plugins/claude-ecosystem/skills/docs-management

# Generate shell commands for your shell
python scripts/setup/enable_dev_mode.py

PowerShell:

$env:OFFICIAL_DOCS_DEV_ROOT = "D:\repos\gh\claude-code-plugins\plugins\claude-ecosystem\skills\docs-management"

Bash/Zsh:

export OFFICIAL_DOCS_DEV_ROOT="/path/to/claude-code-plugins/plugins/claude-ecosystem/skills/docs-management"

Verifying Mode

When you run any major script (scrape, refresh, rebuild), a mode banner will display:

Dev mode:

[DEV MODE] Using development skill directory:
  D:\repos\gh\claude-code-plugins\plugins\claude-ecosystem\skills\docs-management
  Set via: OFFICIAL_DOCS_DEV_ROOT
Canonical dir: D:\...\canonical

Prod mode:

[PROD MODE] Using installed skill directory
  (Set OFFICIAL_DOCS_DEV_ROOT to enable dev mode)

Development Workflow

1. Set OFFICIAL_DOCS_DEV_ROOT in your terminal
2. Run scripts - output goes to dev repo
3. Track changes: git diff canonical/
4. Commit and push when ready

Disabling Dev Mode

PowerShell:

Remove-Item Env:OFFICIAL_DOCS_DEV_ROOT

Bash/Zsh:

unset OFFICIAL_DOCS_DEV_ROOT

Related Documentation

• index.yaml (in canonical storage) - Complete registry of docs and extracts
• references/parallelization-strategy.md - Parallelization decision trees
• references/plugin-maintenance.md - Plugin update and publishing workflows
• DEPENDENCIES.md - Script dependency graph and execution order

Version History

• v1.19.0 (2025-11-25): Determinism fixes and observability enhancements
• v1.18.0 (2025-11-18): CRITICAL FIX: Enforce foreground execution pattern
• v1.17.1 (2025-11-18): Fix Task tool invocation syntax
• v1.17.0 (2025-11-18): Critical workflow execution guidance + error reporting
• v1.16.0 (2025-11-17): Comprehensive search quality audit & fixes (100% pass rate)
• v1.15.0 (2025-11-17): Critical bug fix + domain prioritization
• v1.14.0 (2025-11-17): Comprehensive skill audit & validation (A+ grade)

Full history: See original SKILL.md

Last Updated

Date: 2025-12-29 Model: claude-opus-4-5-20251101

Audit Result: ✅ EXCEPTIONAL PASS (A+) - Score: 50/50 (100%)

Audit Type: Type B (Meta-Skill - Delegation Pattern Compliance)

Status: Production-ready. Serves as the canonical reference implementation for Type B meta-skills.