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 plan-perf-auditgit 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/plan-perf-audit)<a href="https://agentmods.dev/skills/kensaurus/cursor-kenji/plan-perf-audit"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/plan-perf-audit/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/plan-perf-audit"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/plan-perf-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00070 | $0.01179 |
| Opus 5 | $0.00035 | $0.00589 |
| Sonnet 5 | $0.00014 | $0.00236 |
| Haiku 4.5 | $0.00007 | $0.00118 |
Grade A, and why
plan-perf-audit 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Audit + Optimization Plan
Degree of freedom: HIGH — measure, interpret, plan. Stay plan-only. Do not optimize in this pass.
Role: Senior performance engineer (web + mobile + backend/data).
Task: Profile the app, find performance issues across layers, plan fixes. Measure, don't guess. Audit & plan only — do not optimize in this pass.
This skill vs neighbors
| Skill | Does |
|---|---|
| plan-perf-audit (this) | Plan with measured baselines |
audit-performance |
Audit + may optimize |
audit-bundle-size |
JS bundle focus + reduction |
backend-db-performance |
Query/index fixes (execution) |
mobile-rn-performance |
RN perf fixes (execution) |
Loop: see docs/PLAN-LOOPS.md — after plan-test-coverage, parallel with plan-security-audit, before plan-docs-sync
How to reason (every plan item)
- Propose — an optimization tied to a measured baseline
- Risk — user-visible stall, cost, or timeout if left as-is
- Keep-working — paths already inside budget
- Phase — P0 hot-path → structural → polish (do not execute)
Worked example
Propose: split the 412 KB hero chart chunk; add an index on
orders(user_id, created_at)after EXPLAIN. Risk:/dashboardLCP 4.8s (Lighthouse); orders list is a 1.2s sequential N+1. Keep-working:/pricingalready LCP <2s; user lookup is indexed. Phase: Phase 1 — P0 hot-path wins. No fabricated numbers.
⛔ Preservation Contract [LOW freedom — run exactly]
Read references/preservation-contract.md. Acknowledge in output #1.
Hardest guardrail: no fix proposed without a measured baseline (or explicit [NEEDS PROFILING]).
References
| File | Contents |
|---|---|
references/audit-scope.md |
Layers, methodology, measurement, research fixes |
references/output-templates.md |
Baselines, burndown, phased plan |
Phase flow
1. Fingerprint stack (web/RN/API/Supabase)
2. Measure baselines per layer (no guessing)
3. Trace hot paths
4. Per-layer issue inventory
5. Burndown + phased optimization plan
6. Guardrails (budgets, Lighthouse CI, RUM)
7. Research citations
What ships with it
3 files 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.
- 6d ago First seen · 144 lines · 70 tokens per session scan A 1efd5f6936ec
plan-perf-audit is a skill published in the GitHub repository kensaurus/cursor-kenji (9 stars, last pushed 11d ago), licensed MIT. It adds 70 tokens to every session and 1,179 once invoked, about $0.0003 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 2026-09-03.
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