qa-embedding-system
CommunityComprehensive end-to-end QA for BigMac embedding and semantic-search stack
Authorammonfife
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides a comprehensive health-check of the BigMac embedding and semantic-search stack, ensuring data integrity, model consistency, and functional sanity across the entire pipeline.
Core Features & Use Cases
- Embedding Pipeline Health: Checks daemon health, model load state, data integrity, vector-space consistency, embedding coverage, and knowledge-search functionality.
- Orphan Embeddings Detection: Identifies orphan embeddings resulting from deleted source rows but remaining embeddings rows.
- Term Signals and Session Files Freshness: Verifies the freshness of term signals and session files for optimal data integrity.
- Supersession Leakage Check: Ensures there is no leakage of superseded content in search results.
- Quick-Run Gap Finder: Offers a dedicated Python script for quick data-gap audit and potential auto-fixes.
Quick Start
Run the qa-embedding-system skill to perform a full health-check of the BigMac embedding and semantic-search stack.
Dependency Matrix
Required Modules
pythontursolms
Components
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: qa-embedding-system Download link: https://github.com/ammonfife/sakima.co/archive/main.zip#qa-embedding-system Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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