Why are scripts required for index management?

The documentation index can exceed context limits. The skill uses dedicated Python scripts to manage large files efficiently and avoid path doubling issues in PowerShell.

Can I search for documentation using regular language?

Yes, the skill supports natural language queries as well as keyword-based searches and category filtering to find exactly what you need.

How does this skill save on LLM token costs?

It uses subsection extraction to isolate and provide only the relevant parts of a document, typically saving 60-90% on context usage compared to reading entire files.

Does this skill require an active internet connection?

Internet access is only required for the initial scraping of documentation. Once documentation is indexed locally, search and resolution functions work offline.

Codex CLI Documentation

Name: Codex CLI Documentation
Author: melodic-software

bymelodic-software

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Learning & Documentation

Manages and explores official OpenAI Codex CLI documentation through automated indexing, scraping, and token-optimized search.

About

The Codex CLI Documentation skill acts as a centralized librarian for all OpenAI Codex CLI resources, providing high-efficiency search and management tools directly within your workflow. It automates the ingestion of documentation from llms.txt sources and maintains a local metadata index to enable rapid discovery via natural language or keywords. By utilizing intelligent subsection extraction, the skill minimizes context usage by 60-90%, ensuring you only pay for the specific documentation sections you need while maintaining a single, resilient source of truth.

Key Features

Automated scraping from OpenAI Codex CLI llms.txt sources
Token-optimized markdown subsection extraction for reduced context costs
Comprehensive index management with support for aliases and metadata
Hash-based drift detection to identify documentation updates and link rot
Natural language and keyword-based documentation discovery
1 GitHub stars

Use Cases

Finding specific Codex CLI configuration steps using natural language queries
Maintaining an offline-accessible, searchable repository of official OpenAI documentation
Resolving stable documentation IDs to local file paths for resilient referencing

About

Key Features

Automated scraping from OpenAI Codex CLI llms.txt sources
Token-optimized markdown subsection extraction for reduced context costs
Comprehensive index management with support for aliases and metadata
Hash-based drift detection to identify documentation updates and link rot
Natural language and keyword-based documentation discovery
1 GitHub stars

Use Cases

Finding specific Codex CLI configuration steps using natural language queries
Maintaining an offline-accessible, searchable repository of official OpenAI documentation
Resolving stable documentation IDs to local file paths for resilient referencing