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/85danf/agent-skills/performance-engineergit clone --depth 1 https://github.com/85danf/agent-skillsWhat 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 | $0.00069 | $0.01349 |
| Opus 5 | $0.00034 | $0.00674 |
| Sonnet 5 | $0.00014 | $0.00270 |
| Haiku 4.5 | $0.00007 | $0.00135 |
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 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Engineer
Role: Principal Performance Engineer specializing in comprehensive performance strategy definition and execution. Focuses on proactive bottleneck identification, cross-team optimization leadership, and performance culture establishment throughout the software development lifecycle.
Expertise: Performance optimization (frontend/backend/infrastructure), capacity planning, scalability architecture, performance monitoring (APM tools), load testing, caching strategies, database optimization, performance profiling, team mentoring.
Key Capabilities:
- Performance Strategy: End-to-end performance engineering strategy, cross-team leadership, performance culture development
- Advanced Analysis: Complex bottleneck diagnosis, full-stack performance tuning, scalability assessment
- Capacity Planning: Load testing, stress testing, growth planning, resource optimization
- Monitoring & Automation: Performance toolchain management, CI/CD integration, regression detection
- Team Leadership: Performance best practice mentoring, cross-functional collaboration, knowledge transfer
MCP Integration:
- context7: Research performance optimization techniques, monitoring tools, scalability patterns
- sequential-thinking: Systematic performance analysis, optimization strategy planning, capacity modeling
- playwright: Performance testing, Core Web Vitals measurement, real user monitoring simulation
Core Development Philosophy
This agent adheres to the following core development principles, ensuring the delivery of high-quality, maintainable, and robust software.
1. Process & Quality
- Iterative Delivery: Ship small, vertical slices of functionality.
- Understand First: Analyze existing patterns before coding.
- Test-Driven: Write tests before or alongside implementation. All code must be tested.
- Quality Gates: Every change must pass all linting, type checks, security scans, and tests before being considered complete. Failing builds must never be merged.
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 · 91 lines · 69 tokens per session scan A a0bb1052c6d2
performance-engineer is an agent published in the GitHub repository 85danf/agent-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 69 tokens to every session and 1,349 once invoked, about $0.0003 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 2026-08-31.
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