dspy-rag-pipeline
This skill should be used when the user asks to "build a RAG pipeline", "create retrieval augmented generation", "use ColBERTv2 in DSPy", "set up a retriever in DSPy", mentions "RAG with DSPy", "context retrieval", "multi-hop RAG", or needs to build a DSPy system that retrieves external knowledge to answer questions with grounded, factual responses.
npx skills add majiayu000/claude-skill-registry --skill dspy-rag-pipeline --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# DSPy RAG Pipeline ## Goal Build retrieval-augmented generation pipelines with ColBERTv2 that can be systematically optimized. ## When to Use - Questions require external knowledge - You have a document corpus to search - Need grounded, factual responses - Want to optimize retrieval + generation jointly ## Related Skills - Optimize this pipeline: [dspy-miprov2-optimizer](../dspy-miprov2-optimizer/SKILL.md), [dspy-bootstrap-fewshot](../dspy-bootstrap-fewshot/SKILL.md) - Evaluate results: [dspy-evaluation-suite](../dspy-evaluation-suite/SKILL.md) - Design signatures: [dspy-signature-designer](../dspy-signature-designer/SKILL.md) ## Inputs | Input | Type | Description | |-------|------|-------------| | `question` | `str` | User query | | `k` | `int` | Number of passages to retrieve | | `rm` | `dspy.Retrieve` | Retrieval model (ColBERTv2) | ## Outputs | Output | Type | Description | |--------|------|-------------| | `context` | `list[str]` | Retrieved passages | | `answer` | `str` | Generated response | ## Workflow ### Phase 1: Configure Retrieval ```python import dspy # Configure LM and retriever colbert = dspy.ColBERTv2(url='http://20.102.90.50:2017/wiki17_abstracts') dspy.configure
- Goal
- When to Use
- Related Skills
- Inputs
- Outputs
- Workflow
- Phase 1: Configure Retrieval
- Phase 2: Define Signature
- Phase 3: Build RAG Module
- Phase 4: Use
- Production Example
- Multi-Hop RAG
- Best Practices
- Limitations
What does the dspy-rag-pipeline skill do?
This skill should be used when the user asks to "build a RAG pipeline", "create retrieval augmented generation", "use ColBERTv2 in DSPy", "set up a retriever in DSPy", mentions "RAG with DSPy", "context retrieval", "multi-hop RAG", or needs to build a DSPy system that retrieves external knowledge to answer questions with grounded, factual responses.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill dspy-rag-pipeline --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.