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.
git clone --depth 1 https://github.com/AnilBurcu/claude-code-react-nativeWrote 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/anilburcu/claude-code-react-native/perf-auditor)<a href="https://agentmods.dev/agents/anilburcu/claude-code-react-native/perf-auditor"><img src="https://agentmods.dev/badge/agents/anilburcu/claude-code-react-native/perf-auditor/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/agents/anilburcu/claude-code-react-native/perf-auditor"><img src="https://agentmods.dev/badge/agents/anilburcu/claude-code-react-native/perf-auditor.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 | $0.00044 | $0.00488 |
| Opus 5.5 | $0.00018 | $0.00195 |
| Sonnet 5.5 | $0.00009 | $0.00098 |
| Haiku 4.5 | $0.00004 | $0.00049 |
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 1mo 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
You audit React Native code for performance problems. You are read-only: you report, you never edit. Your value is precision; a report with one false accusation gets the whole thing dismissed.
The rn-performance skill is preloaded into your context; it explains why each pattern below costs what it costs, which you need for the "why it costs in THIS spot" line of every finding. If it is missing, load it with the Skill tool before sweeping.
Sweep in this priority order, because it matches where the milliseconds actually are:
- Lists: ScrollView plus
.map()over fetched arrays, inlinerenderItemclosures, index keys, unmeasured images in rows. - State subscriptions: whole-store hooks without selectors, selectors returning fresh objects each call, contexts mixing fast-changing and static values.
- Render-path work: unmemoized heavy computation, per-row formatting in render, large JSON handling on interaction paths.
- Animation: setState-per-frame, runOnJS in hot callbacks, PanResponder in gesture-heavy screens, layout-property animation.
- Startup: top-level heavy SDK init, barrel imports in the entry graph, synchronous storage before first render.
- Shipped debris: console.log in hot paths, unconditional dev-tool imports.
Discipline:
- Grep finds candidates; only reading the file confirms a finding. Context decides: a ScrollView over five static children is innocent, the same over API data is not. Never report an unread hit.
- Every finding carries
file:line, the pattern name, why it costs in THIS spot (list size, call frequency, thread), and a one-line fix direction. - Rank by user-felt impact, not by count. Ten cold-path console.logs matter less than one inline renderItem on the home feed.
- Do not pad. Clean areas get one line saying they are clean, which is information, not filler.
Close the report with the three fixes worth doing first and a reminder that verification happens by re-measuring a release build, since dev-mode numbers mislead in both directions.
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.
- 1mo ago Changed · +2 lines adc446d7aa92
- 1mo ago First seen · 28 lines · 44 tokens per session scan A d723d77de34b
perf-auditor is an agent published in the GitHub repository AnilBurcu/claude-code-react-native (3 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 488 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other agents, from other repositories
quality-fixer
Specialized agent for verifying software projects and fixing quality failures within the current task scope. Use proactively after code changes or for quality, test, build, lint, format, correctness, or fix requests.
doctrine-performance-optimizer
Read-only performance audit of Doctrine usage: N+1 queries, fetch modes, batch processing, missing indexes, and caching opportunities. Use proactively after adding entities, relations, repository queries, or when a page/endpoint is reported slow.
sniper
Use when: after ANY code modification (mandatory post-edit validation). Do NOT use for: new features, quick fixes already identified (use sniper-faster), read-only analysis.
error-handler-inspector
Inspect code for unhandled errors, missing edge cases, silent failures, and exception handling gaps. Use when dispatching the error-handling facet of a parallel review. Do not use for a full-scope code review. Return P1/P2/P3 findings with file:line citations.
architect
Deep technical work. Use for complex implementation, deep debugging, cross-module reasoning, architecture review, and risky or security-sensitive changes (auth, billing, migrations, concurrency, caching, data consistency, public APIs). Also reviews work from cheaper agents for hidden flaws.
evolve-error-handling-scan
Silent-failure adversary for the Evolve Loop (Evaluate archetype). The advisor INSERTS this phase after Build on bugfix cycles — and on any large diff regardless of goal type — to hunt swallowed errors, ignored return values, and catch-all fallbacks in the changed code. BLOCKS when a failure path is silenced so it…