Automatically fetch and feed full project documentation into your AI agent for context-aware coding and debugging.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install docs-feeder
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install docs-feeder using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Docs Feeder?
Docs Feeder is a developer-centric tool designed to optimize the way AI agents consume technical information. By targeting the llms.txt standard, this skill allows users to instantly provide their AI assistants with a comprehensive, flattened version of library documentation. Whether you are working with React, Next.js, or cloud infrastructure tools, Docs Feeder ensures that your Openclaw Skills workflow is backed by the most relevant and up-to-date technical data available, eliminating manual copy-pasting and search-engine fatigue.
Docs Feeder Use Cases
- Debugging framework-specific errors by providing the latest documentation context.
- Onboarding to new libraries by feeding full technical specs into an AI researcher.
- Resolving versioning conflicts by fetching documentation directly from specific GitHub branches or URLs.
- Streamlining the development of Openclaw Skills by automating documentation gathering for API integrations.
How Docs Feeder Works
- The skill triggers a registry lookup for the requested project among 50+ built-in configurations.
- It executes a priority-based fetch, starting with llms-full.txt, then llms.txt, and falling back to the GitHub README.
- For unlisted projects, it utilizes smart discovery to guess common documentation endpoints like docs.xxx.com.
- It monitors data size to alert the user if the content exceeds 500KB, protecting the AI context window.
- The retrieved documentation is then injected into the agent prompt or saved to a local file for persistent use.
Docs Feeder Setup
To get started with this utility within your Openclaw Skills environment, ensure you have Node.js installed.
# Fetch documentation for a specific framework
node fetch-docs.js nextjs
# Fetch from a custom URL
node fetch-docs.js https://docs.anthropic.com
# Save documentation to a local file
node fetch-docs.js prisma --save
Docs Feeder Data Schema & Taxonomy
Docs Feeder organizes documentation metadata using a structured JSON registry.
| Field | Description |
|---|---|
| url | The base URL of the project documentation. |
| llms | The path to the LLM-friendly text file (e.g., /llms.txt). |
| github | The organization and repository identifier for fallback fetching. |
| local | Path to a local copy of documentation if available. |
Docs Feeder Advanced Features
- Custom documentation registry support via edits to docs-registry.json.
- Raw output mode using the --raw flag for clean data piping.
- Automated discovery patterns for unknown project URLs.
- Built-in list command to view all supported projects and libraries instantly.
SKILL.md
Loading
Related Openclaw Skills
book-fetch
A specialized automation skill for searching, downloading, and archiving ebooks from Anna's Archive directly to MEGA cloud storage.
Personalized News Collector
An intelligent agent skill that analyzes user history to deliver a prioritized, interest-based news report.
Task Engine
A sophisticated multi-agent orchestration engine that uses a state machine to track, dispatch, and monitor complex project tasks across various AI agents.
PC Control
A bridge for controlling Windows GUI environments from Linux-based AI agents using screen capture and peripheral simulation.
gh-standup
Generate concise GitHub standup reports by automatically aggregating merged pull requests and direct commits from repositories or organizations.
GitHub Cred
A comprehensive scoring engine that quantifies GitHub developer influence and contribution quality through a four-tier metric system.
Featured*
