name: gemini-cli-docs description: Single source of truth and librarian for ALL Gemini CLI documentation. Manages local documentation storage, scraping, discovery, and resolution. Use when finding, locating, searching, or resolving Gemini CLI documentation; discovering docs by keywords, category, tags, or natural language queries; scraping from llms.txt; managing index metadata (keywords, tags, aliases); or rebuilding index from filesystem. Run scripts to scrape, find, and resolve documentation. Handles doc_id resolution, keyword search, natural language queries, category/tag filtering, alias resolution, llms.txt parsing, markdown subsection extraction for internal use, hash-based drift detection, and comprehensive index maintenance. allowed-tools: Read, Glob, Grep, Bash

Gemini CLI Documentation Skill

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):

ALWAYS use absolute paths (recommended)
Use separate commands (never cd with &&)
Run from repository root with relative paths

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

CRITICAL: Large File Handling - MANDATORY SCRIPT USAGE

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

The file exceeds context limits and will cause issues. 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

This skill provides three slash commands for common workflows:

/google-ecosystem:scrape-docs - Scrape Gemini CLI documentation from geminicli.com, then refresh index and validate
/google-ecosystem:refresh-docs - Refresh the local index and metadata without scraping from remote sources
/google-ecosystem:validate-docs - Validate the index and references for consistency and drift without scraping

Overview

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

Canonical storage (encapsulated in skill) - Single source of truth for official docs
Subsection extraction - Token-optimized extracts (60-90% savings)
Drift detection - Hash-based validation against upstream sources
Sync workflows - 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.

When to Use This Skill

This skill should be used when:

Scraping documentation - Fetching docs from geminicli.com llms.txt
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)

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 plugins/google-ecosystem/skills/gemini-cli-docs/scripts/core/scrape_docs.py --llms-txt https://geminicli.com/llms.txt
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

If you recognize these patterns, STOP and correct immediately.

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"

Quick Start

Refresh Index End-to-End (No Scraping)

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

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 plugins/google-ecosystem/skills/gemini-cli-docs/scripts/management/manage_index.py refresh

Scrape All Documentation

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

# Scrape from llms.txt
python plugins/google-ecosystem/skills/gemini-cli-docs/scripts/core/scrape_docs.py \
  --llms-txt https://geminicli.com/llms.txt

# Refresh index after scraping (use Python 3.13)
py -3.13 plugins/google-ecosystem/skills/gemini-cli-docs/scripts/management/manage_index.py refresh

With options:

# Skip existing files (incremental update)
python plugins/google-ecosystem/skills/gemini-cli-docs/scripts/core/scrape_docs.py \
  --llms-txt https://geminicli.com/llms.txt \
  --skip-existing

# Filter to specific section
python plugins/google-ecosystem/skills/gemini-cli-docs/scripts/core/scrape_docs.py \
  --llms-txt https://geminicli.com/llms.txt \
  --filter "/docs/"

Find Documentation

# Resolve doc_id to file path
python plugins/google-ecosystem/skills/gemini-cli-docs/scripts/core/find_docs.py resolve <doc_id>

# Search by keywords (default: 25 results)
python plugins/google-ecosystem/skills/gemini-cli-docs/scripts/core/find_docs.py search checkpointing session

# Search with custom limit
python plugins/google-ecosystem/skills/gemini-cli-docs/scripts/core/find_docs.py --limit 10 search tools

# Natural language search
python plugins/google-ecosystem/skills/gemini-cli-docs/scripts/core/find_docs.py query "how to use checkpointing"

# List by category
python plugins/google-ecosystem/skills/gemini-cli-docs/scripts/core/find_docs.py category docs

# List by tag
python plugins/google-ecosystem/skills/gemini-cli-docs/scripts/core/find_docs.py tag cli

Search Options:

Option	Default	Description
`--limit N`	25	Maximum number of results to return
`--no-limit`	-	Return all matching results (no limit)
`--min-score N`	-	Only return results with relevance score >= N
`--fast`	-	Index-only search (skip content grep)
`--json`	-	Output results as JSON
`--verbose`	-	Show relevance scores

Configuration System

The gemini-cli-docs 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
config/filtering.yaml - Content filtering rules
config/tag_detection.yaml - Tag detection patterns
references/sources.json - Documentation sources configuration

Environment Variable Overrides:

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

Full details: references/configuration.md

Dependencies

Required: pyyaml, requests, beautifulsoup4, markdownify, filelock Optional (recommended): spacy with en_core_web_sm model (for keyword extraction)

Check dependencies:

python plugins/google-ecosystem/skills/gemini-cli-docs/scripts/setup/check_dependencies.py

Python Version: Python 3.13 recommended (required for spaCy operations)

Full details: references/dependencies.md

Core Capabilities

1. Scraping Documentation

Fetch documentation from geminicli.com using llms.txt format. Features: llms.txt parsing, HTML to Markdown conversion, automatic metadata tracking, URL-based folder organization.

Guide: references/capabilities/scraping-guide.md

2. Extracting Subsections

Extract specific markdown sections for token-optimized responses. 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 documentation drift via 404 checking and hash comparison. Features: 404 URL detection, missing file detection, content hash comparison, orphaned file detection, cleanup automation.

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, category and tag filtering.

Guide: references/capabilities/discovery-guide.md

5. Index Management and Maintenance

Maintain index metadata, keywords, tags, and rebuild index from filesystem.

Guide: references/capabilities/index-management-guide.md

Workflows

Common maintenance and operational workflows:

Scraping Gemini CLI Documentation - Fetching docs from geminicli.com
Refreshing the Index - Rebuilding metadata after changes
Detecting and Cleaning Drift - Finding and removing stale docs
Adding Documentation Categories - Onboarding new doc sections

Detailed Workflows: references/workflows.md

Metadata & Keyword Audit Workflows

Quick validation:

py -3.13 plugins/google-ecosystem/skills/gemini-cli-docs/scripts/validation/quick_validate.py

Search audit:

py -3.13 plugins/google-ecosystem/skills/gemini-cli-docs/scripts/validation/run_search_audit.py
py -3.13 plugins/google-ecosystem/skills/gemini-cli-docs/scripts/validation/analyze_search_audit.py

Tag configuration audit:

py -3.13 plugins/google-ecosystem/skills/gemini-cli-docs/scripts/validation/audit_tag_config.py

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.

Example:

MSYS_NO_PATHCONV=1 python scripts/core/scrape_docs.py \
    --llms-txt https://geminicli.com/llms.txt \
    --filter "/docs/"

See: references/troubleshooting.md#git-bash-path-conversion

Troubleshooting

spaCy Installation Issues

Problem: spaCy installation fails with Python 3.14+.

Solution: Use Python 3.13:

py -3.13 -m pip install spacy
py -3.13 -m spacy download en_core_web_sm

Unicode Encoding Errors

Status: FIXED - Scripts auto-detect Windows and configure UTF-8 encoding.

404 Errors During Scraping

Status: EXPECTED - Some llms.txt entries may reference docs that don't exist yet. Scripts handle gracefully and continue.

Full troubleshooting: references/troubleshooting.md

Public API

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

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

# Natural language search
docs = find_document("model routing configuration")

# Resolve doc_id to metadata
doc = resolve_doc_id("geminicli-com-docs-checkpointing")

# Get docs by tag
cli_docs = get_docs_by_tag("cli")

# Extract specific section
section = get_document_section("geminicli-com-docs-commands", "Built-in Commands")

# Detect drift
drift = detect_drift(check_404s=True, check_hashes=True)

# Cleanup drift (dry run first)
result = cleanup_drift(clean_404s=True, dry_run=True)

# Refresh index with drift detection
result = refresh_index(check_drift=True, cleanup_drift=False)

Plugin Maintenance

For plugin-specific maintenance workflows:

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 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.

Enabling Dev Mode

PowerShell:

$env:GEMINI_DOCS_DEV_ROOT = "D:\repos\gh\melodic\claude-code-plugins"

Bash/Zsh:

export GEMINI_DOCS_DEV_ROOT="/path/to/claude-code-plugins"

Verifying Mode

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

Dev mode:

[DEV MODE] Using local plugin: D:\repos\gh\melodic\claude-code-plugins

Prod mode:

[PROD MODE] Using installed skill directory

Disabling Dev Mode

PowerShell:

Remove-Item Env:GEMINI_DOCS_DEV_ROOT

Bash/Zsh:

unset GEMINI_DOCS_DEV_ROOT

Documentation Categories

Category	Topics
Get Started	installation, authentication, configuration, quickstart
CLI	commands, settings, themes, checkpointing, telemetry, trusted folders
Core	architecture, tools API, policy engine, memport
Tools	file system, shell, web fetch, web search, memory tool, MCP servers
Extensions	creating, managing, releasing extensions
IDE	VS Code, JetBrains, IDE companion

Gemini CLI Features

Key features documented:

Checkpointing: File state snapshots, session management, rewind
Model Routing: Flash vs Pro selection, automatic routing
Token Caching: Prompt compression, cost optimization
Policy Engine: Security controls, trusted folders
Memport: Memory import/export
MCP Servers: Model Context Protocol integration
Extensions: Plugin system for CLI
Sandbox: Isolated execution environment

Directory Structure

gemini-cli-docs/
  SKILL.md                    # This file (public)
  gemini_docs_api.py          # Public API
  canonical/                  # Documentation storage (private)
    geminicli-com/            # Scraped from geminicli.com
    index.yaml                # Metadata index
    index.json                # JSON mirror
  scripts/                    # Implementation (private)
    core/                     # Scraping, discovery
    management/               # Index management
    maintenance/              # Cleanup, drift detection
    validation/               # Validation scripts
    utils/                    # Shared utilities
    setup/                    # Setup scripts
  config/                     # Configuration
    defaults.yaml             # Default settings
    filtering.yaml            # Content filtering
    tag_detection.yaml        # Tag patterns
  references/                 # Technical documentation (public)
    technical-details.md
    workflows.md
    troubleshooting.md
    plugin-maintenance.md
    configuration.md
    dependencies.md
    capabilities/
      scraping-guide.md
      extraction-guide.md
      change-detection-guide.md
      discovery-guide.md
      index-management-guide.md
  .cache/                     # Cache storage (inverted index)
  logs/                       # Log files

Source

Documentation is scraped from: https://geminicli.com/llms.txt

Test Scenarios

Scenario 1: Keyword Search

Query: "Search for checkpointing documentation" Expected Behavior:

Skill activates on keyword "documentation"
Returns relevant docs from index Success Criteria: User receives matching documentation entries

Scenario 2: Natural Language Query

Query: "How do I configure model routing in Gemini CLI?" Expected Behavior:

Skill activates on "Gemini CLI"
Uses find_docs.py query command Success Criteria: Returns relevant documentation with configuration steps

Scenario 3: Doc ID Resolution

Query: "Resolve geminicli-com-docs-checkpointing" Expected Behavior:

Resolves doc_id to file path
Returns document metadata Success Criteria: User receives full path and document content

Scenario 4: Drift Detection

Query: "Check for stale documentation" Expected Behavior:

Runs drift detection script
Reports 404 URLs, missing files, hash mismatches Success Criteria: User receives drift report with actionable items

Scenario 5: Section Extraction

Query: "Get the 'Built-in Commands' section from the commands doc" Expected Behavior:

Extracts specific section from document
Returns only the requested content Success Criteria: User receives targeted section, not full document

Version History

v2.0.0 (2025-12-05): Full feature parity with docs-management - added maintenance scripts, validation scripts, enhanced API, comprehensive documentation
v1.1.0 (2025-12-01): Added Test Scenarios section
v1.0.0 (2025-11-25): Initial release

Last Updated

Date: 2025-12-05 Model: claude-opus-4-5-20251101

Status: Production-ready with full feature parity to docs-management skill.

gemini-cli-docs