Yusuf Karaaslan
Yusuf Karaaslan's Skill Seekers is an open-source data layer for AI systems. It extracts and analyzes documentation, repositories, PDFs, videos, notebooks, wikis and other sources, then turns them into structured AI skills, RAG knowledge and coding-assistant context for multiple AI platforms.
At a Glance
- Solo developers and open-source maintainers
- Development teams and enterprise engineering organizations
- AI/RAG application builders
- Game-development teams using Unity or Godot
- +2 more
AI Tools by Yusuf Karaaslan
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Skill Seekers
Docs to AI Knowledge Toolkit
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Latest News
Skill Seekers v3.10.0 released: Seeker HUD beta, machine-readable CLI commands, SQLite skill search, MiniMax video input, PDF vector-figure extraction and path-traversal security fix.
Skill Seekers v3.9.0 released with resilient HTML parsing, transient network retries, Whisper fallback, MiniMax vision support and CORS hardening.
Heavybit published Yusuf Karaaslan's interview, Translating Data into AI Skills, describing Skill Seekers' origin, use cases and universal data-layer vision.
v3.5.0 shipped the unified create command, agent-agnostic architecture, marketplace publishing, smart SPA discovery, browser rendering and 3,194+ tests.
Products & Services
Python command-line toolkit that detects, scrapes and analyzes 18 source types; combines sources; optionally enhances them with AI; and packages the result for AI skills, RAG systems and coding assistants.
Model Context Protocol server exposing tools for source scraping, configuration, validation, packaging, enhancement, installation, publishing and vector-database export; the current site advertises 40 tools across 10 categories.
Beta local React/FastAPI web UI for the Skill Seekers toolchain, with screens for creation, skills, configs, workflows, analysis, environment and job history.
CI/CD action for scheduled or on-demand generation and updating of AI knowledge from documentation, repositories, PDFs and local codebases.
Market Position
Skill Seekers positions itself as a broad, source-agnostic and model-agnostic preprocessing/data layer rather than only a documentation scraper or a single-agent skill generator. Its differentiators are 18 input types, code analysis, multi-source merging, 22 output targets, MCP automation and CI/CD publishing. Comparable tools include doc2skill and other documentation-to-agent-skill generators, while RAG frameworks such as LangChain, LlamaIndex and vector databases are adjacent alternatives rather than direct end-to-end equivalents.
Leadership
Founders
Yusuf Karaaslan
Computer Engineering graduate and game developer from Istanbul, Turkey; describes himself as an AI-augmented game developer and AI automation engineer. His public profiles identify experience with Unity, Godot and Python and employment at Spyke Games.
Executive Team
Yusuf Karaaslan
Creator and maintainer
Computer Engineering graduate, game developer and AI automation engineer; public profiles cite Unity, Godot and Python development and Spyke Games experience. Heavybit identifies him as the developer who designed Skill Seekers.
Founding Story
Karaaslan started Skill Seekers after trying to create a complete Claude skill from Steam inventory documentation. Claude skipped or aggressively compressed the source material, so he built a separate system to do the heavy data gathering and preprocessing before sending the resulting knowledge back to Claude. The first version shipped the same night Anthropic announced skills; his stated long-term vision is a universal, model-agnostic, source-agnostic data layer for AI systems.
Business Model
Revenue Model
Open-source MIT-licensed software distributed through GitHub and PyPI. The project accepts GitHub sponsorships and displays sponsor placements; its core CLI is installable without a paid subscription, while users may incur their own AI API, cloud-storage or infrastructure costs.
Pricing Tiers
MIT-licensed open-source package installed with pip; API, MCP, LLM, video, cloud and other capabilities are available through optional extras or user-provided services.
Target Markets
- Solo developers and open-source maintainers
- Development teams and enterprise engineering organizations
- AI/RAG application builders
- Game-development teams using Unity or Godot
- Technical writers, educators and researchers
- Teams operating internal knowledge bases, support bots and skill marketplaces
- Give Claude, Gemini, OpenAI and other agents complete framework or library documentation
- Generate and continuously update RAG pipelines from documentation, repositories, PDFs and other sources
- Create repository-aware context and rules for Cursor, Windsurf, Cline, Continue and other coding assistants
- Understand internal codebases and combine official documentation with implementation examples
- Build auto-updating team knowledge bases and support bots through GitHub Actions
- Analyze game-engine projects, including Unity and Godot workflows