docs-seeker

Aggregate technical documentation from llms.txt, repositories, and web sources.

3|1|Updated Dec 21, 2025

Search Tags:#automation #documentation #repomix #llms.txt #websearch #docs-discovery #parallel-exploration

Ready to run

npx skills add https://github.com/vibery-studio/templates --skill docs-seeker-vibery-studio

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: docs-seeker
Source: https://github.com/vibery-studio/templates/tree/main/skills/docs-seeker
Command: npx skills add https://github.com/vibery-studio/templates --skill docs-seeker-vibery-studio

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Searching and consolidating technical documentation from diverse sources (llms.txt, repositories, and web references) is time-consuming and error-prone. This skill provides an automated, multi-source discovery workflow to deliver cohesive, up-to-date documentation guidance.

Core Features & Use Cases

llms.txt-first discovery to quickly locate AI-friendly documentation sources.
Repository analysis via Repomix to extract structured docs from code bases.
Parallel exploration using multiple Explorer agents for comprehensive coverage.
Fallbacks to researchers for scattered or unavailable sources.
Use Case: A developer needs the latest API docs across versions while comparing migration notes from the core repo.

Quick Start

Request the latest official docs for a library and I will locate llms.txt sources, analyze repository docs when needed, and generate a consolidated, version-aware report.

Frequently Asked Questions about docs-seeker

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I discover technical documentation for a library using llms.txt?▼

To discover technical documentation using llms.txt, the system performs an llms.txt-first search to quickly locate AI-friendly documentation sources, then applies parallel analysis to aggregate cohesive, up-to-date guidance.

What is the best way to consolidate repository documentation across multiple versions?▼

Consolidating repository documentation across multiple versions is best handled by analyzing codebases via Repomix and deploying parallel Explorer agents to generate a structured, version-aware report.

Can I extract official docs directly from a code repository?▼

Yes, you can extract official docs directly from a code repository by using Repomix to analyze the repository structure and pull structured documentation from the source code base.

How does parallel exploration work for finding scattered technical documentation?▼

Parallel exploration for finding scattered technical documentation works by deploying multiple Explorer agents simultaneously, falling back to researchers to comprehensively cover unavailable or scattered sources.

What are the limitations of automated docs discovery?▼

Limitations of automated docs discovery include potential gaps when sources are unavailable or scattered, requiring researcher fallbacks, and the output is constrained by the structured report's sources and limitations metadata.

Does docs-seeker work without external dependencies?▼

Yes, docs-seeker works without external dependencies, utilizing internal references and integrated components to execute its multi-phase workflow for aggregating technical documentation.