How do I install the RAG Vault skill?

Run npx skillmds@latest add robthepcguy/rag-vault in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is RAG Vault safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with RAG Vault?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is RAG Vault free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published RAG Vault?

robthepcguy (@robthepcguy) published this skill. Their other Agent Skills are listed on their SkillMD profile.

RAG Vault by robthepcguy — Agent Skill

Name: RAG Vault
Author: robthepcguy

RAG Vault

Use this when someone asks to "search documents", "query RAG", "ingest file", "ingest PDF", "save web page", "add to knowledge base", or mentions document search, semantic search, vector search, or RAG operations. Covers score interpretation (< 0.3 good, > 0.5 skip), query tips, and ingestion guidance for query_documents, ingest_file, ingest_data tools.

robthepcguy Updated Sep 17, 2026

File contents

RAG Vault Skills

Tools

Tool	Use When
`ingest_file`	Local files (PDF, DOCX, TXT, MD, JSON, JSONL)
`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, just 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

---name: rag-vaultdescription: Use this when someone asks to "search documents", "query RAG", "ingest file", "ingest PDF", "save web page", "add to knowledge base", or mentions document search, semantic search, vector search, or RAG operations. Covers score interpretation (< 0.3 good, > 0.5 skip), query tips, and ingestion guidance for query_documents, ingest_file, ingest_data tools.---# RAG Vault Skills## Tools| Tool | Use When ||------|----------|| `ingest_file` | Local files (PDF, DOCX, TXT, MD, JSON, JSONL) || `ingest_data` | Raw content (HTML, text) with source URL || `query_documents` | Semantic + keyword hybrid search || `delete_file` / `list_files` / `status` | Management |## Search: Core RulesHybrid search combines vector (semantic) and keyword (BM25).### Score InterpretationLower = 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 ExpansionWhen 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 SelectionWhen 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**, just 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 pasteRe-ingest same source to update. Use same source in `delete_file` to remove.## ReferencesFor edge cases and examples:- [html-ingestion.md](references/html-ingestion.md) - URL normalization, SPA handling- [query-optimization.md](references/query-optimization.md) - Query patterns by intent- [result-refinement.md](references/result-refinement.md) - Contradiction resolution, chunking

Frequently asked questions