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 mimfort/rag_for_git --skill performance-reviewgit clone --depth 1 https://github.com/mimfort/rag_for_gitWrote 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/mimfort/rag_for_git/performance-review)<a href="https://agentmods.dev/skills/mimfort/rag_for_git/performance-review"><img src="https://agentmods.dev/badge/skills/mimfort/rag_for_git/performance-review/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/mimfort/rag_for_git/performance-review"><img src="https://agentmods.dev/badge/skills/mimfort/rag_for_git/performance-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 8 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00054 | $0.00565 |
| Opus 5.5 | $0.00022 | $0.00226 |
| Sonnet 5.5 | $0.00011 | $0.00113 |
| Haiku 4.5 | $0.00005 | $0.00056 |
Grade A, and why
performance-review 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Review
In rag-reviewer:review-pr use the PR-session tools above. Standalone (no PR session): use
the session-less tools per the reviewer-grounding block when reviewer is connected and the
index is fresh; otherwise fall back to grep/Read.
Goal
Look only for performance and efficiency risks in the selected changes. Ignore style, architecture, tests, and general correctness unless they materially affect performance.
Prioritize findings such as:
- N+1 queries and repeated remote calls;
- unnecessary loops or repeated work;
- bad asymptotic behavior on hot paths;
- redundant rendering, serialization, parsing, allocations, or avoidable copies;
- missing batching, caching, pagination, or streaming where the diff makes that risk likely;
- blocking I/O or CPU-heavy work on latency-sensitive paths;
- memory growth or large payload handling.
Method
- Read the diff first.
- Open only the nearby code needed to understand whether the changed path is
performance-sensitive. In
rag-reviewer:review-pruse the reviewer MCP tools:read_file,search_code,find_callers. - Prefer concrete findings over vague perf speculation.
- If a concern depends on an assumption, state that assumption explicitly.
- If a path is probably not performance-sensitive, do not invent issues.
Severity
critical/high: likely severe latency, throughput, or resource regression on an important path.medium: meaningful inefficiency or scaling risk that should probably be fixed.low: worthwhile optimization or preventive note, not a blocker.
Output
Return only actionable findings.
Return ONLY the findings JSON used by the review pipeline, with
"category": "performance":
- Calibrate
confidenceagainst a measurable, reproducible effect: a hot path you can point to (loop bound, query inside a loop) → 0.8+; a plausible but data-dependent cost → 0.5–0.7; no measurable/reproducible effect → ≤ 0.4 (drop). Set "category" to "performance"; "side" is always "RIGHT".
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 · 63 lines · 54 tokens per session scan A 02304535d482
performance-review is a skill published in the GitHub repository mimfort/rag_for_git (20 stars, last pushed 6d ago), licensed MIT. It adds 54 tokens to every session and 565 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 2026-08-30.
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Use when analyzing codebase structure, verifying pre-flight policy compliance, tracing transitive dependency closures, or auditing post-edit scope creep.
celmis-search
Search and read code through Celmis instead of grepping or cat-ing whole repositories. Use when you need where a symbol is defined, who calls it, what a file or module contains, how another service does something ("make a DB connection like in service X", "do authorization the way service X does", "how does X load its…
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