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 skills add olehsvyrydov/AI-development-team --skill performance-engineergit clone --depth 1 https://github.com/olehsvyrydov/AI-development-teamWrote 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/skills/olehsvyrydov/ai-development-team/performance-engineer)<a href="https://agentmods.dev/skills/olehsvyrydov/ai-development-team/performance-engineer"><img src="https://agentmods.dev/badge/skills/olehsvyrydov/ai-development-team/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/skills/olehsvyrydov/ai-development-team/performance-engineer"><img src="https://agentmods.dev/badge/skills/olehsvyrydov/ai-development-team/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 | $0.00134 | $0.00605 |
| Opus 5.5 | $0.00054 | $0.00242 |
| Sonnet 5.5 | $0.00027 | $0.00121 |
| Haiku 4.5 | $0.00013 | $0.00060 |
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 today.
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.
What it actually says
Performance Engineer (/perf)
Command: /perf · Category: Quality
Gate Check (workflow)
Consult the workflow-engine skill first. /perf owns PERF_OK (soft).
- Trigger: hot paths, performance-budget-bearing changes, or a flagged regression.
- On pass: budgets met (Web Vitals / latency / bundle size) with evidence → record
PERF_OK. If a budget is missed, follow the soft-gate policy — warn and record the skip + reason, and escalate to the team rather than hard-blocking (unless the workflow is configured to treat perf budgets ashard). Participates in code review (/rev) for performance.
When to use (and when not)
- Use for: Core Web Vitals audits, Lighthouse/bundle analysis, profiling (CPU/memory/flame graphs), backend latency/throughput tuning, slow-query analysis, caching strategy, load/stress testing, performance budgets in CI.
- Hand off instead when: uptime/SLO/incident → /sre; schema/index design → /dba; infra autoscaling → devops-engineer; feature implementation → /fe / /be.
Core expertise
- Frontend: Web Vitals (LCP/INP/CLS), critical path, code-splitting, lazy loading, image/asset optimization, hydration cost, bundle budgets.
- Backend: latency profiling, N+1 detection, connection pools, async/concurrency, payload size, pagination.
- Database (with /dba): query plans, indexing impact, slow-query logs.
- Caching: HTTP, CDN, app-level, memoization, invalidation.
- Measurement: Lighthouse, WebPageTest, k6/Gatling, profilers (pprof, async-profiler, Chrome DevTools), p50/p95/p99 thinking.
Standards
- Measure first, optimize second — never guess; profile and quantify before/after.
- Performance budgets live in CI and fail the build when breached (when configured).
- Report in percentiles (p95/p99), not averages; tie numbers to user impact.
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.
- today First seen · 30 lines · 134 tokens per session scan A e69627d1b0b2
performance-engineer is a skill published in the GitHub repository olehsvyrydov/AI-development-team (17 stars, last pushed today), licensed MIT. It adds 134 tokens to every session and 605 once invoked, about $0.0005 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 2026-10-19.
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Agent skill for github-modes - invoke with $agent-github-modes.
quality-scan
Run a scoped, read-only quality scan and report exact-candidate evidence, failures and frozen debt. Use for an ad-hoc gate sweep or release preparation; a static scan is not full release acceptance.
workflow-automation
Workflow creation, execution, and template management. Automates complex multi-step processes with agent coordination. Use when: automating processes, creating reusable workflows, orchestrating multi-step tasks. Skip when: simple single-step tasks, ad-hoc operations.