Ruflo is an execution and coordination layer for Claude Code and Codex that equips AI coding agents with tools, memory, control loops, sandboxes, and collaboration mechanisms. Developers use it to organize specialized agents into swarms, coordinate workflows, retain knowledge across sessions, and communicate across machines. The catalogue entries are Ruflo’s skills, commands, agents, hooks, and plugin components.
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 ruvnet/ruflo --skill agent-v3-performance-engineergit clone --depth 1 https://github.com/ruvnet/rufloWrote 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/ruvnet/ruflo/agent-v3-performance-engineer)<a href="https://agentmods.dev/skills/ruvnet/ruflo/agent-v3-performance-engineer"><img src="https://agentmods.dev/badge/skills/ruvnet/ruflo/agent-v3-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/ruvnet/ruflo/agent-v3-performance-engineer"><img src="https://agentmods.dev/badge/skills/ruvnet/ruflo/agent-v3-performance-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 39 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00025 | $0.02892 |
| Opus 5.5 | $0.00010 | $0.01157 |
| Sonnet 5.5 | $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 2mo 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- agent-v3-performance-engineer — 100% identical, 0 lines differ
- agent-v3-performance-engineer — 100% identical, 0 lines differ
- agent-v3-performance-engineer — 100% identical, 0 lines differ
- agent-v3-performance-engineer — 97% identical, 4 lines differ
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.
- 2mo ago First seen · 402 lines · 25 tokens per session scan A 010cf448f45e
agent-v3-performance-engineer is a skill published in the GitHub repository ruvnet/ruflo (81,499 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 2,892 once invoked, about $0.0001 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 2026-09-03.
agent-v3-performance-engineer compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| agent-v3-performance-engineerruvnet/ruflo | Skill | 81k | today | MIT | A | 25 | Claude Code |
| release-announcementpaperclipai/paperclip | Skill | 113k | today | MIT | A | 42 | Claude Code, Codex |
| suggestion-boxpaperclipai/paperclip | Skill | 113k | today | MIT | A | 37 | Claude Code, Codex |
| index-refreshpaperclipai/paperclip | Skill | 113k | today | MIT | A | 43 | Claude Code, Codex |
| wiki-ingestpaperclipai/paperclip | Skill | 113k | today | MIT | A | 61 | Claude Code, Codex |
| issue-triagepaperclipai/paperclip | Skill | 113k | today | MIT | A | 48 | Claude Code, Codex |
| agentmailpaperclipai/paperclip | Skill | 113k | today | MIT | A | 30 | Claude Code, Codex |