name: ragie-rag description: | Execute Retrieval-Augmented Generation (RAG) using Ragie.ai. Use this skill whenever the user wants to:

• Search their knowledge base
• Ask questions about uploaded documents
• Upload documents to Ragie
• Retrieve context from Ragie
• Perform grounded answering using stored documents
• List, check status, or delete Ragie documents

This skill manages the full Ragie.ai API lifecycle including ingestion, retrieval, and grounded answer construction. metadata: { "openclaw": { "requires": { "bins": ["python3"], "env": ["RAGIE_API_KEY"], "python": ["requests", "python-dotenv"] }, "credentials": { "primary": "RAGIE_API_KEY", "description": "API key from https://app.ragie.ai" } } }

Ragie.ai RAG Skill (OpenClaw Optimized)

This skill enables grounded question answering using Ragie.ai as a RAG backend.

Ragie handles:

• Document chunking
• Embedding
• Vector indexing
• Retrieval
• Optional reranking

The agent handles:

• Deciding when to ingest
• Triggering retrieval
• Constructing grounded prompts
• Producing final answers

Core Principles

1. Never answer without retrieval.
2. Never hallucinate information not present in retrieved chunks.
3. Always cite the document_name when referencing specific facts.
4. If retrieval returns zero relevant chunks, explicitly say:

   "I don't have that information in the current knowledge base."

5. Do not expose API keys or raw API payloads in final answers.

Deterministic Workflow

Case A — User Provides a File or URL

IF the user provides:

• A file
• A document path
• A PDF/URL to ingest

THEN:

1. Execute ingestion:

   python `skills/scripts/ingest.py` --file <path> --name "<document_name>"
   

   OR

   python `skills/scripts/ingest.py` --url "<url>" --name "<document_name>"
   

2. Capture returned document_id.

3. Poll document status:

   python `skills/scripts/manage.py` status --id <document_id>
   

   Repeat until status == ready.

4. Proceed to Retrieval (Case C).

Case B — User Requests Document Management

List documents

python `skills/scripts/manage.py` list

Check document status

python `skills/scripts/manage.py` status --id <document_id>

Delete a document

python `skills/scripts/manage.py` delete --id <document_id>

Return structured results to the user.

Case C — Retrieval (Grounded Question Answering)

Execute:

python `skills/scripts/retrieve.py` \
  --query "<user_question>" \
  --top-k 6 \
  --rerank

Optional flags:

• --partition <name>
• --filter '{"key":"value"}'

Retrieval Output Format

Expected output:

[
  {
    "text": "...",
    "score": 0.87,
    "document_name": "Policy Handbook",
    "document_id": "doc_abc123"
  }
]