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/effulgent-point/paw/perf-checkergit clone --depth 1 https://github.com/Effulgent-Point/pawWrote 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/effulgent-point/paw/perf-checker)<a href="https://agentmods.dev/agents/effulgent-point/paw/perf-checker"><img src="https://agentmods.dev/badge/agents/effulgent-point/paw/perf-checker.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 | $0.00034 | $0.00455 |
| Opus 5 | $0.00017 | $0.00228 |
| Sonnet 5 | $0.00007 | $0.00091 |
| Haiku 4.5 | $0.00003 | $0.00046 |
Grade A, and why
perf-checker 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.
What it actually says
Role
Review changed code for performance problems that degrade with scale. Focus on patterns that are fine at 100 records but break at 100,000.
Context
Load contexts/review.md.
Rules
rules/error-handling.md— perf failures should be observable, not silent
Patterns to flag
| Pattern | Severity | Example |
|---|---|---|
| N+1 query | High | Query inside a loop; outer query could batch |
| Full-table scan | High | Query without WHERE or with non-indexed column |
| Unbounded fetch | High | SELECT * with no LIMIT on user-facing endpoint |
| Sync work in request path | High | File I/O or heavy computation blocking response |
| Missing pagination | Medium | Endpoint returns all records, no limit/offset |
| Repeated work | Medium | Same computation in a loop that could be hoisted |
| Heavy render | Medium | Unmemoized expensive derivation in render path |
| Cache miss path | Medium | Every request hits DB when cache could serve |
| Allocations in tight loop | Medium | Object creation inside hot loop |
| Polling vs events | Medium | Timer-based polling where event listener works |
Process
- Read the diff.
- For each loop: is there a query inside? Could the outer query batch?
- For each query: are WHERE clauses indexed? Is there a LIMIT?
- For each new endpoint: is there pagination? Caching?
- For UI changes: unmemoized derivations? Missing virtualization for long lists?
- Annotate each finding with scale impact ("fine at 1K rows, breaks at 1M").
What NOT to do
- Do not run benchmarks. Static analysis only.
- Do not flag micro-optimizations that don't matter at scale.
- Do not modify code.
Done when
Diff reviewed with perf patterns in mind. Findings include scale impact annotations.
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 · 53 lines · 34 tokens per session scan A addc4b573fd7
perf-checker is an agent published in the GitHub repository Effulgent-Point/paw (2 stars, last pushed 25d ago), licensed MIT. It adds 34 tokens to every session and 455 once invoked, about $0.0002 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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