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 mgiovani/cc-arsenal --skill review-perfgit clone --depth 1 https://github.com/mgiovani/cc-arsenalWrote 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/mgiovani/cc-arsenal/review-perf)<a href="https://agentmods.dev/skills/mgiovani/cc-arsenal/review-perf"><img src="https://agentmods.dev/badge/skills/mgiovani/cc-arsenal/review-perf/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/mgiovani/cc-arsenal/review-perf"><img src="https://agentmods.dev/badge/skills/mgiovani/cc-arsenal/review-perf.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 | $0.00143 | $0.01977 |
| Opus 5 | $0.00072 | $0.00988 |
| Sonnet 5 | $0.00029 | $0.00395 |
| Haiku 4.5 | $0.00014 | $0.00198 |
Grade A, and why
review-perf 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 10d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Review
Comprehensive performance analysis targeting database query inefficiencies, algorithmic complexity issues, frontend bottlenecks, and resource leaks. Analysis only - identifies problems and suggests optimizations without making code changes.
Constraints
- Analysis only - never modifies, fixes, or commits code, even if asked to "also fix these" mid-run; report the findings and stop
- Static analysis - no runtime profiling, no benchmarking, no load testing
- Pattern-based - Big O and impact estimates are approximate; may miss context-specific issues a profiler would catch
- Not exhaustive - does not guarantee 100% detection; profiling is recommended before acting on critical findings
- Read before claiming - never report a finding in a file that has not actually been read; every finding cites the specific file path and line number it came from
- No invented numbers - counts, query-multiplication estimates, and Big O claims must trace back to code actually read, not generic examples copied from the report template
- Diff-scope confinement - for a PR or commit review, never grep or read a file the diff didn't touch, and never let a pre-existing issue in a touched file masquerade as a PR finding; see Phase 0/2
Scan Workflow
Phase 0: Determine Scan Scope
Parse arguments:
<pr_number>: scan only files changed in that PR (e.g.123,#123)<commit_sha>: scan only files changed in that commit--allor no args: scan entire codebase--scope [database|algorithm|frontend|resources|backend]: focus on specific categories (backend= database + algorithm + resources, excludes frontend)
If PR or commit specified, pull the full diff - not just the file list - so hunk ranges are available for Phase 2's confinement check:
# For PR
gh pr diff <pr_number>
# For commit
git diff-tree -p <commit_sha>
From that diff, extract two things and carry both into Phase 2:
- Changed-file list: the paths after each
+++ b/line. - Hunk ranges per file: each
@@ -a,b +c,d @@header gives the new-file line rangectoc+d-1for that hunk. A file can have multiple hunks.
What ships with it
4 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.
- 10d ago First seen · 131 lines · 143 tokens per session scan A cb7732df9e40
review-perf is a skill published in the GitHub repository mgiovani/cc-arsenal (8 stars, last pushed yesterday), licensed MIT. It adds 143 tokens to every session and 1,977 once invoked, about $0.0007 per session on Opus 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 2026-08-31.
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