Borrowing it
Nothing to install: this file belongs to diillson/chatcli. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/diillson/chatcli/main/.agent/agents/performance-optimizer.mdgit clone --depth 1 https://github.com/diillson/chatcliWrote 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/diillson/chatcli/performance-optimizer)<a href="https://agentmods.dev/agents/diillson/chatcli/performance-optimizer"><img src="https://agentmods.dev/badge/agents/diillson/chatcli/performance-optimizer/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/agents/diillson/chatcli/performance-optimizer"><img src="https://agentmods.dev/badge/agents/diillson/chatcli/performance-optimizer.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00053 | $0.01068 |
| Opus 5.5 | $0.00021 | $0.00427 |
| Sonnet 5.5 | $0.00011 | $0.00214 |
| Haiku 4.5 | $0.00005 | $0.00107 |
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 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.
This is a copy
89% identical to performance-optimizer — 32 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 — 188 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.
- 1mo ago First seen · 188 lines · 53 tokens per session scan A 967089346570
performance-optimizer is an agent published in the GitHub repository diillson/chatcli (93 stars, last pushed today), licensed Apache-2.0. It adds 53 tokens to every session and 1,068 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to performance-optimizer, differing in 32 lines, and is treated as a copy.
Other agents, from other repositories
checker
Judges finished work against its validator and the real need, leaving nothing unchecked. Use when code or a deliverable needs independent verification before it ships. Never edits the work, never implements the fix.
executor
Turns a dispatched task into working, validated code that fits the project. Use when an approved scope must become code. Never plans, never judges its own work.
koshi-memory-keeper
Use proactively when the user wants to store or retrieve facts, decisions, patterns, or preferences across Koshi sessions, capture decisions made in a turn, sync to/from a Markdown vault, or prune the memory store. Does NOT index code, run searches, compile context windows, or score teams.
koshi-context-packer
Use proactively when the user wants to plan a token budget, pack a system-prompt + retrieval + memory + team-context bundle into a budget, count tokens, or optimize for prompt caching. May read from retrieval and memory tools to assemble content. Does NOT index, store memories, or score teams.
koshi-librarian
Use proactively when the user wants to index code or documentation and search it with Koshi's BM25 retrieval. Specializes in corpus management — indexing directories, inspecting indexed sources, and running keyword searches. Does NOT manage memories, compile context windows, or score teams.
Demonstrate
Agent for demonstrating VS Code features.