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 MasihMoafi/rag-mcp --skill rag-searchgit clone --depth 1 https://github.com/MasihMoafi/rag-mcpWrote 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/masihmoafi/rag-mcp/rag-search)<a href="https://agentmods.dev/skills/masihmoafi/rag-mcp/rag-search"><img src="https://agentmods.dev/badge/skills/masihmoafi/rag-mcp/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/masihmoafi/rag-mcp/rag-search"><img src="https://agentmods.dev/badge/skills/masihmoafi/rag-mcp/rag-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00049 | $0.00257 |
| Opus 5.5 | $0.00020 | $0.00103 |
| Sonnet 5.5 | $0.00010 | $0.00051 |
| Haiku 4.5 | $0.00005 | $0.00026 |
Grade A, and why
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 yesterday.
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.
What it actually says
rag-search
Use the query_knowledge_base tool from the rag MCP server.
- Pick the smallest file or subdirectory likely to hold the answer and pass it as
doc_path. Never point it at a repository or workspace root by default. - Ask a specific question. If the evidence is thin, retry with exact terms or synonyms before widening the scope.
- For "is X mentioned anywhere" or coverage claims, ask several differently worded questions; one miss is not proof of absence.
- On a scan-limit error, narrow
doc_pathand continue. - Use
extensions(for example[".md"]) to filter a directory by file type.
To inspect or change the pipeline (embedding model, reranker, number of passages), use get_rag_settings / set_rag_settings, or the /rag command. Never put API keys in chat; the user runs rag setup in a terminal.
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.
- yesterday First seen · 17 lines · 49 tokens per session scan A 4270d2fdc8be
rag-search is a skill published in the GitHub repository MasihMoafi/rag-mcp (7 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 257 once invoked, about $0.0002 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 2026-10-16.
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