gitbook-example-1-documentation-site-builder
Sub-skill of gitbook: Example 1: Documentation Site Builder (+2).
Best use case
gitbook-example-1-documentation-site-builder is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of gitbook: Example 1: Documentation Site Builder (+2).
Teams using gitbook-example-1-documentation-site-builder should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/example-1-documentation-site-builder/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How gitbook-example-1-documentation-site-builder Compares
| Feature / Agent | gitbook-example-1-documentation-site-builder | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of gitbook: Example 1: Documentation Site Builder (+2).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Example 1: Documentation Site Builder (+2)
## Example 1: Documentation Site Builder
```python
#!/usr/bin/env python3
"""docs_site_builder.py - Build complete documentation site"""
import os
from datetime import datetime
import json
class DocsSiteBuilder:
"""Build and manage GitBook documentation sites."""
*See sub-skills for full details.*
## Example 2: Content Migration Tool
```python
#!/usr/bin/env python3
"""content_migration.py - Migrate content to GitBook"""
import os
from pathlib import Path
import re
import shutil
class ContentMigrator:
*See sub-skills for full details.*
## Example 3: Documentation Analytics
```python
#!/usr/bin/env python3
"""docs_analytics.py - GitBook documentation analytics"""
import os
from datetime import datetime, timedelta
import json
class DocsAnalytics:
"""Analyze GitBook documentation usage."""
*See sub-skills for full details.*Related Skills
handle-browser-automation-financial-site-blocks
Workflow for working around Chrome extension blocks on financial sites during data collection tasks
handle-blocked-financial-sites-workaround
Workflow for accessing financial account data when browser automation is blocked on brokerage sites
handle-blocked-financial-sites-data-export
Workflow for extracting data from blocked financial sites when browser automation is restricted
financial-site-bypass-workflow
Workflow for accessing restricted financial sites when browser automation is blocked
static-site-build-artifact-plan-review
Plan-review pattern for static-site fixes where the deployed artifact is generated from source files (e.g. sitemap/robots/static assets). Prevents review churn by separating durable regression checks from one-time migration verification and by validating built output, not just source files.
static-site-brand-identity-migration-tdd
Execute approved static-site brand identity/logo migrations with TDD across canonical content sources, generated deploy output, legacy checked-in HTML, existing stale tests, and build/docs contracts.
gtm-site-readiness-audit-local-vs-production
Audit GTM feature work by separating local artifact readiness from production deployment state, then fix common blockers in aceengineer-website and GTM collateral.
documentation-contract-plan-hardening
Harden a documentation/contract plan before adversarial review by mapping every issue-scope requirement to independent acceptance criteria and tests, especially for routing/indexing contracts.
mcp-builder
Guide for building high-quality Model Context Protocol (MCP) servers that allow LLMs to interact with external services. Use when creating new MCP integrations, tools, or servers for Codex or other AI systems.
rag-system-builder
Build Retrieval-Augmented Generation (RAG) Q&A systems with Codex or OpenAI. Use for creating AI assistants that answer questions from document collections, technical libraries, or knowledge bases.
knowledge-base-builder
Build searchable knowledge bases from document collections (PDFs, Word, text files). Use for creating technical libraries, standards repositories, research databases, or any large document collection requiring full-text search.
interactive-dashboard-builder
Create self-contained HTML/JavaScript dashboards with Chart.js, filters, and professional styling