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 monkilabs/opencastle --skill performance-optimizationgit clone --depth 1 https://github.com/monkilabs/opencastleWrote 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/monkilabs/opencastle/performance-optimization)<a href="https://agentmods.dev/skills/monkilabs/opencastle/performance-optimization"><img src="https://agentmods.dev/badge/skills/monkilabs/opencastle/performance-optimization/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/monkilabs/opencastle/performance-optimization"><img src="https://agentmods.dev/badge/skills/monkilabs/opencastle/performance-optimization.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 | $0.00052 | $0.00362 |
| Opus 5 | $0.00026 | $0.00181 |
| Sonnet 5 | $0.00010 | $0.00072 |
| Haiku 4.5 | $0.00005 | $0.00036 |
Grade A, and why
performance-optimization 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.
What it actually says
Performance Optimization
Measure before changing anything. Add React.memo/useMemo/useCallback only after a profile shows the cost — never speculatively. Set budgets (load time, memory, API latency) and enforce them in CI.
Rules
- Node: async APIs only — never
readFileSyncor other sync I/O on a request path. - Debounce input-driven fetches at 300 ms.
- INP replaced FID as a Core Web Vital in March 2024: budget it at ≤200 ms, and measure every interaction, not just the first.
- Profile Node with
clinic.jsornode --inspect; profile React with<Profiler onRender>or the DevTools Profiler.
Profiling Workflow
- Lighthouse (or the CI perf job) for a baseline; name the failing metric (LCP/CLS/INP/TTI). Lighthouse emulates mobile by default; pass
--preset=desktopwhen the regression is desktop-only. - Profile to locate the hotspot call stacks / long tasks.
- Apply the minimal fix (code-split, memoize, shrink payloads, defer non-critical work); confirm in the profiler that the measured hotspot actually shrank.
- Re-run Lighthouse / the CI perf job. Ship only at ≥10% improvement or once inside budget.
- If the regression persists, iterate and record a rollback plan; note fixes in the changelog.
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 · 24 lines · 52 tokens per session scan A 495dbbdaaee6
performance-optimization is a skill published in the GitHub repository monkilabs/opencastle (61 stars, last pushed 12d ago), licensed MIT. It adds 52 tokens to every session and 362 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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