MCP Local RAG Skills

mcp-local-rag

Provides score interpretation (< 0.3 good, > 0.5 skip), query optimization, and source naming for query_documents, ingest_file, ingest_data tools. Use this skill when working with RAG, searching documents, ingesting files, saving web content, or handling PDF, HTML, DOCX, TXT, Markdown.

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SKILL.md

Full skill instructions

MCP Local RAG Skills

Tools

Tool	Use When
`ingest_file`	Local files (PDF, DOCX, TXT, MD)
`ingest_data`	Raw content (HTML, text) with source URL
`query_documents`	Semantic + keyword hybrid search
`delete_file` / `list_files` / `status`	Management

Search: Core Rules

Hybrid search combines vector (semantic) and keyword (BM25).

Score Interpretation

Lower = better match. Use this to filter noise.

Score	Action
< 0.3	Use directly
0.3-0.5	Include if mentions same concept/entity
> 0.5	Skip unless no better results

Limit Selection

Intent	Limit
Specific answer (function, error)	5
General understanding	10
Comprehensive survey	20

Query Formulation

Situation	Why Transform	Action
Specific term mentioned	Keyword search needs exact match	KEEP term
Vague query	Vector search needs semantic signal	ADD context
Error stack or code block	Long text dilutes relevance	EXTRACT core keywords
Multiple distinct topics	Single query conflates results	SPLIT queries
Few/poor results	Term mismatch	EXPAND (see below)

Query Expansion

When results are few or all score > 0.5, expand query terms:

Keep original term first, add 2-4 variants
Types: synonyms, abbreviations, related terms, word forms
Example: "config" → "config configuration settings configure"

Avoid over-expansion (causes topic drift).

Result Selection

When to include vs skip—based on answer quality, not just score.

INCLUDE if:

Directly answers the question
Provides necessary context
Score < 0.5

SKIP if:

Same keyword, unrelated context
Score > 0.7
Mentions term without explanation

Ingestion

ingest_file

ingest_file({ filePath: "/absolute/path/to/document.pdf" })

ingest_data

ingest_data({
  content: "<html>...</html>",
  metadata: { source: "https://example.com/page", format: "html" }
})

Format selection — match the data you have:

HTML string → format: "html"
Markdown string → format: "markdown"
Other → format: "text"

Source format:

Web page → Use URL: https://example.com/page
Other content → Use scheme: {type}://{date} or {type}://{date}/{detail}
- Examples: clipboard://2024-12-30, chat://2024-12-30/project-discussion

HTML source options:

Static page → LLM fetch
SPA/JS-rendered → Browser MCP
Auth required → Manual paste

Re-ingest same source to update. Use same source in delete_file to remove.

References

For edge cases and examples:

html-ingestion.md - URL normalization, SPA handling
query-optimization.md - Query patterns by intent
result-refinement.md - Contradiction resolution, chunking

Install skill

Copy and run in your terminal

npx -y skills add https://github.com/majiayu000/claude-skill-registry-data --skill mcp-local-rag

View on GitHub

data/mcp-local-rag/SKILL.md

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