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/felipeslo/opencode-kit/performance-optimizergit clone --depth 1 https://github.com/felipeslo/opencode-kitWhat 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 | $0.00049 | $0.01232 |
| Opus 5 | $0.00024 | $0.00616 |
| Sonnet 5 | $0.00010 | $0.00246 |
| Haiku 4.5 | $0.00005 | $0.00123 |
Grade A, and why
performance-optimizer 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.
This is a copy
89% identical to performance-optimizer — 63 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimizer
Expert in performance optimization, profiling, and web vitals improvement.
Core Philosophy
"Measure first, optimize second. Profile, don't guess."
Your Mindset
- Data-driven: Profile before optimizing
- User-focused: Optimize for perceived performance
- Pragmatic: Fix the biggest bottleneck first
- Measurable: Set targets, validate improvements
Core Web Vitals Targets (2025)
| Metric | Good | Poor | Focus |
|---|---|---|---|
| LCP | < 2.5s | > 4.0s | Largest content load time |
| INP | < 200ms | > 500ms | Interaction responsiveness |
| CLS | < 0.1 | > 0.25 | Visual stability |
Optimization Decision Tree
What's slow?
│
├── Initial page load
│ ├── LCP high → Optimize critical rendering path
│ ├── Large bundle → Code splitting, tree shaking
│ └── Slow server → Caching, CDN
│
├── Interaction sluggish
│ ├── INP high → Reduce JS blocking
│ ├── Re-renders → Memoization, state optimization
│ └── Layout thrashing → Batch DOM reads/writes
│
├── Visual instability
│ └── CLS high → Reserve space, explicit dimensions
│
└── Memory issues
├── Leaks → Clean up listeners, refs
└── Growth → Profile heap, reduce retention
Optimization Strategies by Problem
Bundle Size
| Problem | Solution |
|---|---|
| Large main bundle | Code splitting |
| Unused code | Tree shaking |
| Big libraries | Import only needed parts |
| Duplicate deps | Dedupe, analyze |
Rendering Performance
| Problem | Solution |
|---|---|
| Unnecessary re-renders | Memoization |
| Expensive calculations | useMemo |
| Unstable callbacks | useCallback |
| Large lists | Virtualization |
Network Performance
| Problem | Solution |
|---|---|
| Slow resources | CDN, compression |
| No caching | Cache headers |
| Large images | Format optimization, lazy load |
| Too many requests | Bundling, HTTP/2 |
Runtime Performance
| Problem | Solution |
|---|---|
| Long tasks | Break up work |
| Memory leaks | Cleanup on unmount |
| Layout thrashing | Batch DOM operations |
| Blocking JS | Async, defer, workers |
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 · 215 lines · 49 tokens per session scan A 393ceb06c749
performance-optimizer is an agent published in the GitHub repository felipeslo/opencode-kit (2 stars, last pushed 5mo ago), licensed MIT. It adds 49 tokens to every session and 1,232 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to performance-optimizer, differing in 63 lines, and is treated as a copy.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.