Borrowing it
Nothing to install: this file belongs to MikahNiehaus/ClaudeBoost. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/MikahNiehaus/ClaudeBoost/main/.claude/commands/fix-rag.mdgit clone --depth 1 https://github.com/MikahNiehaus/ClaudeBoostWrote 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/commands/mikahniehaus/claudeboost/fix-rag)<a href="https://agentmods.dev/commands/mikahniehaus/claudeboost/fix-rag"><img src="https://agentmods.dev/badge/commands/mikahniehaus/claudeboost/fix-rag/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/commands/mikahniehaus/claudeboost/fix-rag"><img src="https://agentmods.dev/badge/commands/mikahniehaus/claudeboost/fix-rag.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 | $0.00013 | $0.01329 |
| Opus 5.5 | $0.00005 | $0.00532 |
| Sonnet 5.5 | $0.00003 | $0.00266 |
| Haiku 4.5 | $0.00001 | $0.00133 |
Grade B, and why
fix-rag scanned grade B with 2 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 8d 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
curl -s -X POST http://127.0.0.1:8613/search -H "Content-Type: application/json" -d '{"query":"test","sources":["project:<abs path>"],"mode":"both","limit":1}' Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s --connect-timeout 5 http://127.0.0.1:8613/status The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 8d ago First seen · 142 lines · 13 tokens per session scan B ad877ba1276b
fix-rag is a command published in the GitHub repository MikahNiehaus/ClaudeBoost (9 stars, last pushed yesterday), with no licence file. It adds 13 tokens to every session and 1,329 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-02.
Other commands, from other repositories
rag-audit
Report quality and best-practice gaps in an existing implementation. TRIGGER WHEN: the user asks to review, audit, or validate a RAG pipeline: chunking, embeddings, retrieval, reranking, or production readiness. DO NOT TRIGGER WHEN: building from scratch (use rag-architect), or auditing a pure vector database (use…
rag-debug
Walk the 9-layer RAG failure diagnostic chain against a specific failing query.
rag-failure-trace
Capture a full RAG audit trace for a query — useful for debugging or seeding a regression test.
review-code
Review code for quality, security, and maintainability. Dispatches all relevant reviewer agents in parallel and merges findings by severity.
rag-debug
Debug RAG pipeline issues with systematic retrieval and generation analysis.
querying
Query documents from a search index using type-safe filters with support for pagination, sorting, field selection, scoring, and highlighting. Count matching documents efficiently without returning results.