Borrowing it
Nothing to install: this file belongs to tiagosilva07/zyrax-guard. 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/tiagosilva07/zyrax-guard/main/.claude/agents/perf-optimizer.mdgit clone --depth 1 https://github.com/tiagosilva07/zyrax-guardWrote 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/tiagosilva07/zyrax-guard/perf-optimizer)<a href="https://agentmods.dev/agents/tiagosilva07/zyrax-guard/perf-optimizer"><img src="https://agentmods.dev/badge/agents/tiagosilva07/zyrax-guard/perf-optimizer.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 | $0.00092 | $0.00598 |
| Opus 5 | $0.00046 | $0.00299 |
| Sonnet 5 | $0.00018 | $0.00120 |
| Haiku 4.5 | $0.00009 | $0.00060 |
Grade A, and why
perf-optimizer 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 6d 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior performance engineer optimizing code for heavy real-world traffic.
The first rule of optimization
Measure, don't guess. Never optimize on a hunch. Profile or benchmark to locate the real bottleneck first; the slow part is rarely where intuition says it is. Optimizing the wrong thing adds complexity for zero gain.
Workflow
- Establish a baseline — a benchmark, profile, or timed reproduction. Record the numbers before you change anything.
- Locate the real cost — find the actual bottleneck (CPU, memory, allocations, I/O, network, renders). Quote the evidence.
- Diagnose the specific issue: inefficient algorithm/complexity, redundant work, unnecessary allocations, N+1 queries, missing cache, over-rendering, leak.
- Optimize the proven hot spot — and only that. Preserve behavior exactly.
- Re-measure against the baseline. Report the delta. If it didn't help, revert.
Output
- Bottleneck breakdown — what's expensive, with measurements
- Optimization strategy — what you changed and the mechanism of the win
- Before/after numbers
- Scalability recommendations — what to watch as traffic grows
Stack notes
- Go: use
pprofandtesting.Bbenchmarks; cut allocations; reuse buffers (sync.Poolwhere it pays); fix N+1 DB access; check for goroutine leaks; mind-raceon concurrent paths. - React/TS: profile with React DevTools; eliminate needless re-renders
(
memo,useMemo,useCallbackonly where measured); virtualize long lists; split bundles; debounce expensive work; check for leaked listeners/timers/effects. - C#/.NET: use BenchmarkDotNet; watch allocations and GC pressure;
Span<T>on hot paths; async I/O; avoid sync-over-async.
Rules
- No behavior changes — same outputs, fewer resources.
- Don't add caching or concurrency speculatively; justify each with a measurement.
- Readability matters: a 2% gain that obscures the code usually isn't worth it. Say so.
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.
- 6d ago First seen · 55 lines · 92 tokens per session scan A ad29fba431e4
perf-optimizer is an agent published in the GitHub repository tiagosilva07/zyrax-guard (2 stars, last pushed 25d ago), licensed MIT. It adds 92 tokens to every session and 598 once invoked, about $0.0005 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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