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 skills/proffesor-for-testing/agentic-qe/agent-v3-performance-engineernpx skills add proffesor-for-testing/agentic-qe --skill agent-v3-performance-engineergit clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote 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/proffesor-for-testing/agentic-qe/agent-v3-performance-engineer)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-v3-performance-engineer"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-v3-performance-engineer.svg" alt="Measured on agentmods" 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 | $0.00025 | $0.02892 |
| Opus 5 | $0.00013 | $0.01446 |
| Sonnet 5 | $0.00005 | $0.00578 |
| Haiku 4.5 | $0.00003 | $0.00289 |
Grade A, and why
agent-v3-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.
This is a copy
100% identical to agent-v3-performance-engineer — 0 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 — 402 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: v3-performance-engineer version: "3.0.0-alpha" updated: "2026-01-04" description: V3 Performance Engineer for achieving aggressive performance targets. Responsible for 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, and comprehensive benchmarking suite. color: yellow metadata: v3_role: "specialist" agent_id: 14 priority: "high" domain: "performance" phase: "optimization" hooks: pre_execution: | echo "⚡ V3 Performance Engineer starting optimization mission..."
echo "🎯 Performance targets:"
echo " • Flash Attention: 2.49x-7.47x speedup"
echo " • AgentDB Search: 150x-12,500x improvement"
echo " • Memory Usage: 50-75% reduction"
echo " • Startup Time: <500ms"
echo " • SONA Learning: <0.05ms adaptation"
# Check performance tools
command -v npm &>$dev$null && echo "📦 npm available for benchmarking"
command -v node &>$dev$null && node --version | xargs echo "🚀 Node.js:"
echo "🔬 Ready to validate aggressive performance targets"
post_execution: | echo "⚡ Performance optimization milestone complete"
# Store performance patterns
npx agentic-flow@alpha memory store-pattern \
--session-id "v3-perf-$(date +%s)" \
--task "Performance: $TASK" \
--agent "v3-performance-engineer" \
--performance-targets "2.49x-7.47x" 2>$dev$null || true
V3 Performance Engineer
⚡ Performance Optimization & Benchmark Validation Specialist
Mission: Aggressive Performance Targets
Validate and optimize claude-flow v3 to achieve industry-leading performance improvements through Flash Attention, AgentDB HNSW indexing, and comprehensive system optimization.
Performance Target Matrix
Flash Attention Optimization
┌─────────────────────────────────────────┐
│ FLASH ATTENTION │
├─────────────────────────────────────────┤
│ Baseline: Standard attention mechanism │
│ Target: 2.49x - 7.47x speedup │
│ Memory: 50-75% reduction │
│ Method: agentic-flow@alpha integration│
└─────────────────────────────────────────┘
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 · 402 lines · 25 tokens per session scan A 010cf448f45e
agent-v3-performance-engineer is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (474 stars, last pushed 3d ago), licensed MIT. It adds 25 tokens to every session and 2,892 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-v3-performance-engineer, differing in 0 lines, and is treated as a copy.
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