Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nkapila6/mcp-local-rag --skill local-rag-searchgit clone --depth 1 https://github.com/nkapila6/mcp-local-ragWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nkapila6/mcp-local-rag/local-rag-search)<a href="https://agentmods.dev/skills/nkapila6/mcp-local-rag/local-rag-search"><img src="https://agentmods.dev/badge/skills/nkapila6/mcp-local-rag/local-rag-search/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nkapila6/mcp-local-rag/local-rag-search"><img src="https://agentmods.dev/badge/skills/nkapila6/mcp-local-rag/local-rag-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00080 | $0.01482 |
| Opus 5.5 | $0.00032 | $0.00593 |
| Sonnet 5.5 | $0.00016 | $0.00296 |
| Haiku 4.5 | $0.00008 | $0.00148 |
Grade A, and why
local-rag-search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Local RAG Search Skill
This skill enables you to effectively use the mcp-local-rag MCP server for intelligent web searches with semantic ranking. The server performs RAG-like similarity scoring to prioritize the most relevant results without requiring any external APIs.
Available Tools
1. rag_search_ddgs - DuckDuckGo Search
Use this for privacy-focused, general web searches.
When to use:
- User prefers privacy-focused searches
- General information lookup
- Default choice for most queries
Parameters:
query: Natural language search querynum_results: Initial results to fetch (default: 10)top_k: Most relevant results to return (default: 5)include_urls: Include source URLs (default: true)
2. rag_search_google - Google Search
Use this for comprehensive, technical, or detailed searches.
When to use:
- Technical or scientific queries
- Need comprehensive coverage
- Searching for specific documentation
3. deep_research - Multi-Engine Deep Research
Use this for comprehensive research across multiple search engines.
When to use:
- Researching complex topics requiring broad coverage
- Need diverse perspectives from multiple sources
- Gathering comprehensive information on a subject
Available backends:
duckduckgo: Privacy-focused general searchgoogle: Comprehensive technical resultsbing: Microsoft's search enginebrave: Privacy-first searchwikipedia: Encyclopedia/factual contentyahoo,yandex,mojeek,grokipedia: Alternative engines
Default: ["duckduckgo", "google"]
4. deep_research_google - Google-Only Deep Research
Shortcut for deep research using only Google.
5. deep_research_ddgs - DuckDuckGo-Only Deep Research
Shortcut for deep research using only DuckDuckGo.
Best Practices
Query Formulation
- Use natural language: Write queries as questions or descriptive phrases
- Good: "latest developments in quantum computing"
- Good: "how to implement binary search in Python"
- Avoid: Single keywords like "quantum" or "Python"
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 189 lines · 80 tokens per session scan A c5ce423a1c1a
local-rag-search is a skill published in the GitHub repository nkapila6/mcp-local-rag (134 stars, last pushed 1mo ago), licensed MIT. It adds 80 tokens to every session and 1,482 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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