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 agents/christopherlouet/claude-base/qa-perfgit clone --depth 1 https://github.com/christopherlouet/claude-baseWrote 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/agents/christopherlouet/claude-base/qa-perf)<a href="https://agentmods.dev/agents/christopherlouet/claude-base/qa-perf"><img src="https://agentmods.dev/badge/agents/christopherlouet/claude-base/qa-perf.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 | $0.00029 | $0.00419 |
| Opus 5 | $0.00015 | $0.00210 |
| Sonnet 5 | $0.00006 | $0.00084 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
qa-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 3d 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.
What it actually says
Agent QA-PERF
Performance analysis and optimization.
Methodology
- Measure BEFORE: baseline (time, memory, CPU), Core Web Vitals
- Identify bottlenecks: code (O(n2), N+1), frontend (bundle, renders, images), backend (index, cache, pool)
- Optimize by priority: algorithm > caching > lazy loading > parallelization > micro-optimizations
- Measure AFTER: validate the gain
Core Web Vitals
| Metric | Target |
|---|---|
| LCP | < 2.5s |
| FID | < 100ms |
| CLS | < 0.1 |
| TTFB | < 800ms |
| INP | < 200ms |
Patterns to look for
- Nested loops (O(n2))
- console.log in production
- Heavy
*imports - Queries inside loops (N+1)
Expected output
- Performance baseline
- Identified bottlenecks (file:line, problem, impact)
- Proposed optimizations with estimated gain
- Before/after measurements
Guidelines
- NEVER optimize without prior profiling
- IMPORTANT: Measure before and after each optimization
- IMPORTANT: Prioritize by cost/benefit ratio
- NEVER do micro-optimizations before algorithmic gains
Think hard about the real bottlenecks, not premature optimizations.
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.
- 3d ago First seen · 60 lines · 29 tokens per session scan A 28fa9260cea7
qa-perf is an agent published in the GitHub repository christopherlouet/claude-base (5 stars, last pushed 3d ago), licensed MIT. It adds 29 tokens to every session and 419 once invoked, about $0.0001 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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