RuView: Skill for Claude Code

.claude/skills/v3-performance-optimization/SKILL.md

V3 Performance Optimization is a skill for Claude Code from ruvnet/RuView. It costs 53 tokens per session (2,435 once invoked), scanned A, original, MIT.

A performance tuning and benchmarking guide for claude-flow v3, covering attention processing, memory use, and AgentDB search.

In plain words
What is it for?
Use it to establish baselines, test Flash Attention speed, measure search improvements, and reduce memory consumption.
Why use it?
It helps locate slow or resource-heavy parts of the system and measure whether optimizations meet defined targets.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is ruvnet/RuView's own configuration. It tells Claude Code how to work on RuView itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything RuView configures →

About the project

RuView is a WiFi sensing platform that uses disturbances in radio signals, captured by low-cost ESP32 sensors, to detect presence, movement, breathing, and heart rate without cameras or wearables. It is intended for spatial monitoring and smart-home integrations. The catalogue add-ons support workflows for operating and integrating RuView.

ruvnet/RuView · 98,818 stars · on GitHub · cognitum.one

Reuse

Borrowing it

Nothing to install: this file belongs to ruvnet/RuView. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ruvnet/RuView/main/.claude/skills/v3-performance-optimization/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/ruvnet/RuView

Made for: Claude Code.

Wrote 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.

agentmods badge for V3 Performance Optimization

README.md
[![agentmods](https://agentmods.dev/badge/skills/ruvnet/ruview/v3-performance-optimization/github.svg)](https://agentmods.dev/skills/ruvnet/ruview/v3-performance-optimization)
Your own site
<a href="https://agentmods.dev/skills/ruvnet/ruview/v3-performance-optimization"><img src="https://agentmods.dev/badge/skills/ruvnet/ruview/v3-performance-optimization/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.

agentmods 80×15 button for V3 Performance Optimization

Your own site · 80×15
<a href="https://agentmods.dev/skills/ruvnet/ruview/v3-performance-optimization"><img src="https://agentmods.dev/badge/skills/ruvnet/ruview/v3-performance-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,435 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00053 $0.02435
Opus 5.5 $0.00021 $0.00974
Sonnet 5.5 $0.00011 $0.00487
Haiku 4.5 $0.00005 $0.00244

Measured 1mo ago against content hash 25858e4c4325, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

V3 Performance Optimization 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.

Origin

Copies of this mod

8 near-identical copies found in the catalogue:

.claude/skills/v3-performance-optimization/SKILL.md · 390 lines

How it starts

The opening of the file, as written. The whole thing — 390 lines — stays where its author put it; the contents beside it link to each section on GitHub.

V3 Performance Optimization

What This Skill Does

Validates and optimizes claude-flow v3 to achieve industry-leading performance through Flash Attention, AgentDB HNSW indexing, and comprehensive system optimization with continuous benchmarking.

Quick Start

# Initialize performance optimization
Task("Performance baseline", "Establish v2 performance benchmarks", "v3-performance-engineer")

# Target validation (parallel)
Task("Flash Attention", "Validate 2.49x-7.47x speedup target", "v3-performance-engineer")
Task("Search optimization", "Validate 150x-12,500x search improvement", "v3-performance-engineer")
Task("Memory optimization", "Achieve 50-75% memory reduction", "v3-performance-engineer")

Performance Target Matrix

Flash Attention Revolution

┌─────────────────────────────────────────┐
│           FLASH ATTENTION               │
├─────────────────────────────────────────┤
│  Baseline: Standard attention           │
│  Target:   2.49x - 7.47x speedup       │
│  Memory:   50-75% reduction             │
│  Latency:  Sub-millisecond processing   │
└─────────────────────────────────────────┘

Search Performance Revolution

┌─────────────────────────────────────────┐
│            SEARCH OPTIMIZATION         │
├─────────────────────────────────────────┤
│  Current:  O(n) linear search           │
│  Target:   150x - 12,500x improvement   │
│  Method:   HNSW indexing                │
│  Latency:  <100ms for 1M+ entries       │
└─────────────────────────────────────────┘

Comprehensive Benchmark Suite

Startup Performance

class StartupBenchmarks {
  async benchmarkColdStart(): Promise<BenchmarkResult> {
    const startTime = performance.now();

    await this.initializeCLI();
    await this.initializeMCPServer();
    await this.spawnTestAgent();

    const totalTime = performance.now() - startTime;

    return {
      total: totalTime,
      target: 500, // ms
      achieved: totalTime < 500
    };
  }
}

Read the full file on GitHub · 390 lines

Changes

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.

  1. 1mo ago First seen · 390 lines · 53 tokens per session scan A 25858e4c4325

Subscribe to this mod's changes

V3 Performance Optimization is a skill published in the GitHub repository ruvnet/RuView (98,818 stars, last pushed today), licensed MIT. It adds 53 tokens to every session and 2,435 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 2026-09-03.

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