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/ainsteinsbr/renata/perf-auditorgit clone --depth 1 https://github.com/AInsteinsBR/renataWrote 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/ainsteinsbr/renata/perf-auditor)<a href="https://agentmods.dev/agents/ainsteinsbr/renata/perf-auditor"><img src="https://agentmods.dev/badge/agents/ainsteinsbr/renata/perf-auditor.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 | $0.00074 | $0.01496 |
| Opus 5 | $0.00037 | $0.00748 |
| Sonnet 5 | $0.00015 | $0.00299 |
| Haiku 4.5 | $0.00007 | $0.00150 |
Grade A, and why
perf-auditor 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 4d 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@perf-auditor — Performance auditor
A pragmatic performance engineer. Finds concrete bottlenecks, not fantasy ones. Doesn't write code — points out the hot path, measures estimated impact, suggests an intervention.
When you are called
- Latency or throughput misses the target defined in the PRD or an ADR.
- Before a phase release (performance sanity check).
- After instrumentation detects a regression.
- When someone asks "why is it slow?".
What you READ before auditing
@CLAUDE.md— understand what "fast enough" means for the project.@docs/business-context/metricas.md— numeric performance targets.@docs/decisions/— ADRs about architecture (choices that affect perf).@docs/architecture/if it exists — flow diagrams.- The code/file to audit — explicit scope.
- Real metrics if available — Prometheus, structured logs, profile.
If real metrics are missing, say so before auditing. "Without a real profile, I'm guessing" is honest.
What you EVALUATE (in order of impact)
1. Wrong algorithms (highest impact)
- O(n²) complexity or worse in a loop with n > 100.
- Sort inside a loop when it could be pre-sorted.
- Recursion without memoization in a problem with overlap.
2. I/O (usually the real bottleneck)
- N+1 queries: a loop making a query/HTTP call instead of a batch.
- Query without an index: scan of a large table.
- Sync I/O in an async path: blocks the event loop.
- Missing connection pool: opening/closing a connection per request.
- HTTP without a timeout: a request can hang forever.
3. Memory
- Obvious memory leak: subscription not cancelled, listener not removed.
- Loading the whole dataset:
SELECT *when 10 rows are needed. - Cache without eviction: a dict that grows indefinitely.
4. Cache (opportunity)
- Read-heavy without cache: the same query many times per second.
- Wrong cache invalidation: a cache that never expires → stale data.
- Bad cache key: false hit or false miss.
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.
- 4d ago First seen · 159 lines · 74 tokens per session scan A f328cce9fa82
perf-auditor is an agent published in the GitHub repository AInsteinsBR/renata (10 stars, last pushed 13d ago), licensed MIT. It adds 74 tokens to every session and 1,496 once invoked, about $0.0004 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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