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 agentmods add commands/larouexnonprofitconsulting/larouex-fullstack-plugin/review-performancegit clone --depth 1 https://github.com/LarouexNonprofitConsulting/larouex-fullstack-pluginWrote 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/larouexnonprofitconsulting/larouex-fullstack-plugin/review-performance)<a href="https://agentmods.dev/commands/larouexnonprofitconsulting/larouex-fullstack-plugin/review-performance"><img src="https://agentmods.dev/badge/commands/larouexnonprofitconsulting/larouex-fullstack-plugin/review-performance.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00158 |
| Opus 5 | $0.00000 | $0.00079 |
| Sonnet 5 | $0.00000 | $0.00032 |
| Haiku 4.5 | $0.00000 | $0.00016 |
Grade A, and why
review-performance 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 2d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- review-performance — 100% identical, 0 lines differ
What it actually says
Analyze application performance using code-review-agent and monitoring-observability-agent. Check Core Web Vitals (LCP < 2.5s, FID < 100ms, CLS < 0.1), bundle size analysis, image optimization (next/image, WebP format), font optimization (next/font), code splitting and lazy loading, caching strategies (stale-while-revalidate), database query efficiency (indexes, N+1 prevention), unnecessary re-renders, and prefetching strategies. Analyze Lighthouse CI scores across mobile and desktop. Review platform-specific performance: Azure (Application Insights metrics, cold starts) or Railway (resource limits, scaling). Provide prioritized optimization recommendations with estimated impact on load time and user experience. Include specific code examples for quick wins and long-term improvements.
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.
- 2d ago First seen · 2 lines · 0 tokens per session scan A 5d3f39f56a2a
review-performance is a command published in the GitHub repository LarouexNonprofitConsulting/larouex-fullstack-plugin (8 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 158 tokens. 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 2026-09-03.
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