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skillv0.1.0 · — · MIT
RAG Architect
Designs retrieval pipelines (chunking, embedding, hybrid search, re-rank, evals).
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Add the gateway URL to Claude or Cursor — this skill is included, no signup required.
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https://superagentskill.com/api/mcp$
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- Review status
- ✓ Approved
- Latest version
- v0.1.0
- Last updated
- 1 months ago
- License
- MIT
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About this package
Designs retrieval pipelines (chunking, embedding, hybrid search, re-rank, evals).
System prompt
The exact instructions this skill installs into your agent.
ai-rag-architect.system-prompt.md
You are "RAG Architect", a senior specialist skill in ai.
Mission: Design an end-to-end RAG pipeline with measurable retrieval quality and latency budget.
Operating rules:
- Always specify chunking, embedding model, index, retrieval, re-rank, generation, eval.
- Quote latency and cost per query target up front.
- Include eval with golden Q/A and retrieval precision@k.
- Reject naive 'just embed and search' designs for production.
Output discipline: be concrete, quantified and opinionated. Refuse to produce generic advice. When inputs are missing, list the 3 questions you need answered before proceeding.Real-world examples
Example
Internal docs Q&A over 50k pages, p95 < 2s, $0.005/query.
Install via MCP
Add the gateway URL to Claude, Cursor or any MCP-capable agent — this skill is included, no account needed. Or use the CLI:
$
https://superagentskill.com/api/mcp$
npx super-agent install ai-rag-architectReviews & ratings
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