Skill Seekers converts documentation, code repositories, PDFs, videos, notebooks, and other sources into structured knowledge assets for AI skills, retrieval systems, and coding assistants. Developers use it to prepare source material for tools such as Claude, Gemini, OpenAI, LangChain, LlamaIndex, Cursor, Windsurf, and Cline, with exports for multiple targets. The catalogue entries provide skills, commands, instructions, an MCP integration, and a plugin for using the project.
Borrowing it
Nothing to install: this file belongs to yusufkaraaslan/Skill_Seekers. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/yusufkaraaslan/Skill_Seekers/development/AGENTS.mdgit clone --depth 1 https://github.com/yusufkaraaslan/Skill_SeekersWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/yusufkaraaslan/skill_seekers/agents-md)<a href="https://agentmods.dev/instructions/yusufkaraaslan/skill_seekers/agents-md"><img src="https://agentmods.dev/badge/instructions/yusufkaraaslan/skill_seekers/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/yusufkaraaslan/skill_seekers/agents-md"><img src="https://agentmods.dev/badge/instructions/yusufkaraaslan/skill_seekers/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.03868 | $0.03868 |
| Opus 5.5 | $0.01547 | $0.01547 |
| Sonnet 5.5 | $0.00774 | $0.00774 |
| Haiku 4.5 | $0.00387 | $0.00387 |
Grade A, and why
Skill_Seekers AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 17d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md - Skill Seekers
Comprehensive reference for AI coding agents. Skill Seekers is a Python CLI tool (v3.6.0) that converts documentation sites, GitHub repos, PDFs, videos, notebooks, wikis, and more into AI-ready skills for 21+ LLM platforms and RAG pipelines.
Project Overview
Skill Seekers is a universal preprocessing layer that transforms raw documentation and code into structured knowledge assets. It supports 17+ source types and exports to 21+ AI platforms including Claude, Gemini, OpenAI, LangChain, LlamaIndex, and various vector databases.
Key Capabilities
- Source Types (17): Documentation websites, GitHub repos, PDFs, Word docs, EPUBs, videos, local codebases, Jupyter notebooks, HTML, OpenAPI specs, AsciiDoc, PowerPoint, Confluence, Notion, RSS feeds, man pages, chat exports
- Export Targets (21): Claude, Gemini, OpenAI, MiniMax, OpenCode, Kimi, DeepSeek, Qwen, OpenRouter, Together AI, Fireworks AI, Markdown, LangChain, LlamaIndex, Haystack, Weaviate, ChromaDB, FAISS, Qdrant, Pinecone
- MCP Server: FastMCP-based Model Context Protocol server for AI assistant integration
Setup
# REQUIRED before running tests (src/ layout — tests hard-exit if package not installed)
pip install -e .
# With dev tools (pytest, ruff, mypy, coverage)
pip install -e ".[dev]"
# With specific LLM platform support
pip install -e ".[gemini]" # Google Gemini
pip install -e ".[openai]" # OpenAI ChatGPT
pip install -e ".[all-llms]" # All LLM platforms
# With all optional dependencies (except video-full)
pip install -e ".[all]"
# Full video processing (heavy dependencies)
pip install -e ".[video-full]"
Note: tests/conftest.py checks that skill_seekers is importable and calls sys.exit(1) if not. Always install in editable mode first.
Environment Variables
Create a .env file or export these variables:
ANTHROPIC_API_KEY # For Claude AI enhancement
GOOGLE_API_KEY # For Gemini support
OPENAI_API_KEY # For OpenAI support
GITHUB_TOKEN # For GitHub repo scraping (higher rate limits)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 17d ago Changed · +2 lines · +47 tokens per session e542c425f66b
- 27d ago Changed · +2 lines · +65 tokens per session 23b77b9d4168
- 1mo ago Changed · +22 lines · +285 tokens per session 5ba594382a04
- 1mo ago First seen · 304 lines · 3,471 tokens per session scan A 80d1396ad9ea
Skill_Seekers AGENTS.md is an instructions file published in the GitHub repository yusufkaraaslan/Skill_Seekers (15,174 stars, last pushed 17d ago), licensed MIT. It adds 3,868 tokens to every session, about $0.0155 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).