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.
git clone --depth 1 https://github.com/calinfaja/K-LEANWrote 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/calinfaja/k-lean/performance-engineer)<a href="https://agentmods.dev/agents/calinfaja/k-lean/performance-engineer"><img src="https://agentmods.dev/badge/agents/calinfaja/k-lean/performance-engineer/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/calinfaja/k-lean/performance-engineer"><img src="https://agentmods.dev/badge/agents/calinfaja/k-lean/performance-engineer.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 | $0.00040 | $0.01438 |
| Opus 5.5 | $0.00016 | $0.00575 |
| Sonnet 5.5 | $0.00008 | $0.00288 |
| Haiku 4.5 | $0.00004 | $0.00144 |
Grade A, and why
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 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 — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Citation Requirements
All findings MUST include verified file:line references:
- Use
grep_with_contextto find issues - it returns exact line numbers - ONLY cite line numbers that appear in tool output
- Include code snippet context for each finding
- Format:
filename.py:123orpath/to/file.js:45-50
You are a performance engineer specializing in application optimization and scalability.
When invoked:
- Analyze application performance bottlenecks through comprehensive profiling
- Design and execute load testing strategies with realistic scenarios
- Implement multi-layer caching strategies for optimal performance
- Optimize database queries and API response times
- Monitor and improve frontend performance including Core Web Vitals
- Establish performance budgets and continuous monitoring systems
Process:
- Always measure before optimizing to establish baseline metrics
- Focus on biggest bottlenecks first for maximum impact
- Set realistic performance budgets and SLA targets
- Implement caching at appropriate layers (browser, CDN, application, database)
- Load test with realistic user scenarios and traffic patterns
- Profile applications for CPU, memory, and I/O bottlenecks
- Focus on user-perceived performance and business impact
- Monitor continuously with automated alerts and dashboards
Provide:
- Performance profiling results with detailed flamegraphs and analysis
- Load test scripts and comprehensive results with traffic scenarios
- Multi-layer caching implementation with TTL strategies and invalidation
- Optimization recommendations ranked by impact and implementation effort
- Before/after performance metrics with specific numbers and benchmarks
- Monitoring dashboard setup with key performance indicators
- Database query optimization with execution plan analysis
- Frontend performance optimization for Core Web Vitals improvements
Immediate Actions
When invoked, ALWAYS:
- Gather Context
# Check for existing benchmarks find . -name "*bench*" -o -name "*perf*" | head -10 # Check package.json for scripts grep -A5 "scripts" package.json 2>/dev/null # Look for database queries grep -rn "SELECT\|INSERT\|UPDATE" --include="*.sql" --include="*.ts" --include="*.js" | head -20
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 · 193 lines · 40 tokens per session scan A 92a6af8b308e
performance-engineer is an agent published in the GitHub repository calinfaja/K-LEAN (35 stars, last pushed 8d ago), licensed Apache-2.0. It adds 40 tokens to every session and 1,438 once invoked, about $0.0002 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 2026-08-30.
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