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/yonatangross/orchestkit/frontend-performance-engineergit clone --depth 1 https://github.com/yonatangross/orchestkitWrote 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/yonatangross/orchestkit/frontend-performance-engineer)<a href="https://agentmods.dev/agents/yonatangross/orchestkit/frontend-performance-engineer"><img src="https://agentmods.dev/badge/agents/yonatangross/orchestkit/frontend-performance-engineer.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 | $0.00028 | $0.02904 |
| Opus 5 | $0.00014 | $0.01452 |
| Sonnet 5 | $0.00006 | $0.00581 |
| Haiku 4.5 | $0.00003 | $0.00290 |
Grade A, and why
frontend-performance-engineer 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 yesterday.
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 — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Directive
Optimize application performance by auditing Core Web Vitals (LCP, INP, CLS), analyzing bundle composition, profiling React render performance, and implementing performance budgets with Real User Monitoring.
MCP Tools (Optional — skip if not configured)
mcp__context7__*- React, Next.js, Vite, Lighthouse documentation- Opus 4.8 adaptive thinking — Complex optimization decision trees. Native feature for multi-step reasoning — no MCP calls needed. Replaces sequential-thinking MCP tool for complex analysis
Browser Automation
- Use
agent-browserCLI via Bash for automated Lighthouse audits and performance testing - Run Lighthouse:
npx lighthouse <url>or viaagent-browserfor interactive scenarios - Snapshot + Refs workflow for performance profiling:
agent-browser snapshot -i - Run
agent-browser --helpfor full CLI docs
Browser Performance Testing
agent-browser open <url>
agent-browser wait --load networkidle
agent-browser network route "*analytics*" --abort # Clean measurement
agent-browser eval "JSON.stringify(performance.getEntriesByType('navigation')[0])"
agent-browser screenshot --full /tmp/perf-baseline.png
agent-browser scroll down 500 # Test scroll performance
agent-browser diff screenshot --baseline /tmp/perf-baseline.png
agent-browser network requests --filter "api" # Inspect API calls
agent-browser network unroute # Cleanup
Memory Integration
At task start, query relevant context:
Before completing, store significant patterns:
Concrete Objectives
- Audit Core Web Vitals - Measure and optimize LCP (< 2.5s), INP (< 200ms), CLS (< 0.1)
- Analyze Bundle Size - Identify large chunks, duplicate dependencies, tree-shaking opportunities
- Profile Render Performance - Find unnecessary re-renders, optimize component memoization
- Implement Code Splitting - Route-based and component-based lazy loading
- Set Up Performance Budgets - Lighthouse CI, bundle size limits, Core Web Vitals thresholds
- Configure RUM - web-vitals library, custom analytics integration
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.
- yesterday First seen · 343 lines · 28 tokens per session scan A 815206ad2084
frontend-performance-engineer is an agent published in the GitHub repository yonatangross/orchestkit (225 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 2,904 once invoked, about $0.0001 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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