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 ericrisco/rsc-harness --skill performancegit clone --depth 1 https://github.com/ericrisco/rsc-harnessWrote 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/ericrisco/rsc-harness/performance)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/performance"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/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/ericrisco/rsc-harness/performance"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/performance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Prompt Injection · line 80 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- medium MCP Rug Pull · line 151 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 | $0.00091 | $0.03907 |
| Opus 5.5 | $0.00036 | $0.01563 |
| Sonnet 5.5 | $0.00018 | $0.00781 |
| Haiku 4.5 | $0.00009 | $0.00391 |
Grade A, and why
performance 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.
How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance: make one thing fast
Performance makes a single request, page, or interaction faster for one user. Scaling makes many requests survive at the same time. Different problem, different toolbox — if the system is fine for you and only bends under concurrent load, that is ../scaling/SKILL.md, not this.
The whole job in one line: measure with a profiler → attribute the cost to one specific phase → apply the one fix that moves that phase → re-measure against a number. Repeat until you clear the threshold, then stop.
Prime directive: no fix without a profile first. A waterfall, a flame chart, a bundle treemap, or a field CWV number comes before you touch code. The fix you guess is almost never the fix the measurement points at, and a "fast" change that moves a phase nobody was waiting on is wasted work that you then have to maintain.
Cross-reference, don't duplicate: the last column of the table below names where each deep fix lives. The one case it has no row for — you decided what to cache to cut a phase and now need that cache race-free — is ../redis/SKILL.md.
Decision table — symptom to first move
| Symptom | Metric / phase | First probe | First lever | Deep fix lives in |
|---|---|---|---|---|
| Slow load, hero appears late | LCP | Lighthouse + DevTools trace | attribute to a subpart, then fix that one | this skill / ../postgresdb/SKILL.md if TTFB |
| Janky scroll, laggy typing/click | INP | DevTools Performance trace (long-task bars) | break the >50 ms task, yield | this skill |
| Layout jumps as it loads | CLS | Lighthouse layout-shift trace | reserve space (dimensions / aspect-ratio) | this skill |
| "First Load JS is huge" | bundle bytes | @next/bundle-analyzer / source-map-explorer |
kill/replace the heavy dep, then dynamic import | this skill |
| Component re-renders constantly | render time | React DevTools Profiler ("why did this render") | fix the unstable ref / boundary | ../react/SKILL.md for the pattern |
'use client' drags server work down |
First Load JS | bundle analyzer server/client trace | push the boundary to a leaf | ../nextjs/SKILL.md |
| Slow only under concurrent load | throughput, not latency | load test | — not this skill — | ../scaling/SKILL.md |
| TTFB dominated by one query | server time | query plan / EXPLAIN |
— not this skill — | ../postgresdb/SKILL.md |
What ships with it
4 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.
- 1mo ago First seen · 230 lines · 91 tokens per session scan A ffbdecc1e453
performance is a skill published in the GitHub repository ericrisco/rsc-harness (231 stars, last pushed yesterday), licensed MIT. It adds 91 tokens to every session and 3,907 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
nextjs-optimization
Optimize images, fonts, scripts, and metadata for Next.js performance and Core Web Vitals. Use when configuring next/image for LCP, next/font for zero layout shift, next/script loading strategies, or generateMetadata for SEO.
react-performance-debugging
Diagnose and fix slow catalog, cart, compare-page, and API-route performance issues in Next.js by targeting upstream fetch patterns, non-blocking side effects, bundle size, and unnecessary rerenders without breaking required test hooks or instrumentation.
performance-optimization
Use when performance requirements exist, profiling reveals bottlenecks, or Core Web Vitals need improvement. Do NOT use without evidence — premature optimization adds complexity.
optimize
On-demand performance and optimization analysis. Use when identifying bottlenecks, improving build times, reducing bundle size, or optimizing code performance. Trigger keywords - "optimize", "performance", "bottleneck", "bundle size", "build time", "speed up".
performance-engineer
!cat skills/shared/protocols/ux-protocol.md 2>/dev/null || true !cat .production-grade.yaml 2>/dev/null || echo "No config — using defaults".
performance-optimization
Use this skill when optimizing application performance across frontend (Core Web Vitals, bundles), backend (N+1 queries, connection pools, caching), and database (indexes, query plans). Profiles before fixing, pinpoints actual bottlenecks rather than assumed ones, verifies improvements by re-measuring the same way as…