Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Add context gate and post-retrieval relevance filter to reduce noise from irrelevant RAG chunks
What This Skill Does
Fabrik-Codek is a personal cognitive architecture that runs locally with any Ollama model. It builds a knowledge graph from your work sessions, profiles your expertise per topic, and routes queries to the right retrieval strategy. Responses feed back into the system to adjust future retrieval.
Unlike generic RAG setups, it tracks your actual expertise level per topic and adjusts retrieval depth and model selection accordingly, without requiring manual feedback.
When to use it
- Finding past code patterns by semantic meaning
- Getting context-aware answers based on your own session history
- Checking how concepts in your stack relate to each other
- Searching for exact terms across accumulated knowledge
- Monitoring which topics you have deep vs shallow coverage on
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: 'How should I handle database connection pooling in my stack?'
- 1Task Router classifies the query as an architecture/design task and detects the database topic
- 2Competence Model looks up the user's expertise score for that topic
- 3Retrieval strategy is selected: hybrid vector + graph search given moderate competence
- 4Knowledge graph is traversed for entities related to connection pooling in the user's history
- 5A personalized system prompt is assembled and sent to the local Ollama model
A context-aware answer drawing on the user's own past decisions and patterns, with retrieval parameters logged for outcome tracking
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.