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 skills add kensaurus/cursor-kenji --skill audit-performancegit clone --depth 1 https://github.com/kensaurus/cursor-kenjiWrote 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/skills/kensaurus/cursor-kenji/audit-performance)<a href="https://agentmods.dev/skills/kensaurus/cursor-kenji/audit-performance"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/audit-performance/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/skills/kensaurus/cursor-kenji/audit-performance"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/audit-performance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 108 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 144 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00069 | $0.03958 |
| Opus 5.5 | $0.00028 | $0.01583 |
| Sonnet 5.5 | $0.00014 | $0.00792 |
| Haiku 4.5 | $0.00007 | $0.00396 |
Grade A, and why
audit-performance scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sv https://example.com/ 2>&1 | grep -E "< HTTP/.* 103" How it starts
The opening of the file, as written. The whole thing — 384 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Audit Skill
Degree of freedom: MIXED — what to optimize [HIGH freedom];
measure-first Sentry/vitals and EXPLAIN [LOW freedom — run exactly].
Audit-and-fix exception. Measure, then optimize. JS payload →
audit-bundle-size. Instant navigations →enhance-web-instant-nav. Breaking point →test-load. Timeouts/retries →audit-resilience. When fixing: change only the measured bottleneck and re-measure it; log other slow paths you notice as follow-ups, not fixes. Edit the existing file in place rather than rewriting it. Add a perf test only where the repo already keeps them or the task asks; scratch measurements stay out of the repo.
How to reason
- Observe — quote LCP/INP/CLS, p95, or
EXPLAIN/ N+1 loop (file:line) - Interpret — is the user waiting on bytes, a query, or main-thread work?
- Classify — vital-miss / N+1 / missing-index / bundle / image / re-render
- Severity — poor LCP/INP or p95 >> target on a live path = Critical
Worked example
Observe: Sentry p95
/users= 2.3s; handlerfindAllthen per-userOrder.findByUserId(app/api/users/route.ts:31). Interpret: N+1; TTFB/LCP suffer on that page. Classify: N+1. Severity: Critical (p95 far over 200ms). Finding:/users| N+1 | eager-load orders | then re-measure
Step 0: Gather Performance Data [LOW freedom — run exactly]
Before optimizing, measure. Collect data from multiple sources.
Production Data (Sentry)
If Sentry performance monitoring is enabled, fetch real production metrics:
sentry:search_events
{
"organizationSlug": "<ORG_SLUG>",
"projectSlug": "<PROJECT_SLUG>",
"regionUrl": "<REGION_URL>",
"query": "slowest transactions by p95 duration in last 7 days",
"limit": 20
}
sentry:search_events
{
"organizationSlug": "<ORG_SLUG>",
"projectSlug": "<PROJECT_SLUG>",
"regionUrl": "<REGION_URL>",
"query": "web vitals LCP INP CLS performance scores in last 7 days",
"limit": 20
}
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · -6 tokens per session 15c0742ffe64
- 1mo ago First seen · 382 lines · 75 tokens per session scan A 2b10f0762e55
audit-performance is a skill published in the GitHub repository kensaurus/cursor-kenji (9 stars, last pushed 26d ago), licensed MIT. It adds 69 tokens to every session and 3,958 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering bugs, test failures, unexpected behavior, or any technical issue before proposing fixes.
debug-issue
Systematically debug a reported issue.
incident-triage-harness
Production-style incident triage workflow for logs, metrics, code, safe mitigations, and M3 multimodal visual evidence (screenshots, screen recordings). Use when debugging alerts, regressions, outages, or suspicious runtime behavior.
fix-issue
Fix a GitHub issue end-to-end. Use when given an issue number to fix, implementing bug fixes, or addressing reported problems.
agent-self-verification
A code-change verification workflow that builds the project, checks the interface and logs, and repeats fixes when something fails.
test-reporting-triage-skill
Automatically categorizes test failures, suggests responsible owners, and provides common fix checklists. Generates actionable test reports with failure analysis. Use for "test reporting", "failure triage", "test analysis", or "test automation".