CtrlK
BlogDocsLog inGet started
Tessl Logo

agent-v3-performance-engineer

Agent skill for v3-performance-engineer - invoke with $agent-v3-performance-engineer

Install with Tessl CLI

npx tessl i github:ruvnet/claude-flow --skill agent-v3-performance-engineer
What are skills?

35

3.20x

Does it follow best practices?

Evaluation96%

3.20x

Agent success when using this skill

Validation for skill structure

SKILL.md
Review
Evals

Evaluation results

90%

71%

Benchmark Suite: Attention Mechanism & Vector Search

Attention and search benchmark targets

Criteria
Without context
With context

Attention speedup target range

0%

100%

Attention memory reduction target

0%

100%

Attention sequence lengths

0%

100%

Attention result structure

62%

100%

Search improvement target range

0%

100%

Search achieved flag

37%

100%

Search test query count

0%

100%

Search result structure

50%

75%

Memory usage tracking

50%

100%

Memory reduction target

0%

100%

Memory result structure

50%

66%

Sub-100ms latency note

0%

0%

Without context: $0.2798 · 1m 31s · 14 turns · 21 in / 5,606 out tokens

With context: $0.5294 · 2m 3s · 20 turns · 182 in / 7,779 out tokens

100%

82%

Agent CLI Startup & Adaptive Learning Benchmarks

Startup and SONA adaptation benchmarks

Criteria
Without context
With context

Startup target 500ms

62%

100%

Startup return fields

40%

100%

SONA target 0.05ms

0%

100%

hrtime.bigint() for SONA

0%

100%

SONA scenario: pattern_recognition

0%

100%

SONA scenario: task_optimization

0%

100%

SONA scenario: error_correction

0%

100%

SONA scenario: performance_tuning

0%

100%

SONA scenario: behavior_adaptation

0%

100%

agentic-flow store-pattern command

0%

100%

store-pattern flags present

0%

100%

SONA result structure

16%

100%

SONA successRate field

100%

100%

Without context: $0.2938 · 1m 41s · 14 turns · 21 in / 5,230 out tokens

With context: $0.4665 · 1m 40s · 23 turns · 60 in / 5,300 out tokens

100%

47%

Performance Monitoring Dashboard & Regression Detection System

Regression detection and performance monitoring

Criteria
Without context
With context

MetricCollector key: flash_attention_speedup

0%

100%

MetricCollector key: search_improvement

0%

100%

MetricCollector key: memory_reduction

0%

100%

MetricCollector key: startup_time

0%

100%

MetricCollector key: sona_adaptation

0%

100%

5% regression threshold

50%

100%

Regression return: hasRegressions

100%

100%

Regression return: regressions array

100%

100%

Regression return: recommendations

100%

100%

PerformanceReport: summary field

100%

100%

PerformanceReport: achievements field

0%

100%

PerformanceReport: recommendations field

0%

100%

PerformanceReport: trends field

0%

100%

PerformanceReport: nextActions field

0%

100%

15-agent swarm benchmark

100%

100%

Swarm: 3 timing measurements

100%

100%

Without context: $0.4602 · 2m 26s · 20 turns · 26 in / 8,648 out tokens

With context: $0.5985 · 2m 31s · 23 turns · 101 in / 9,538 out tokens

Evaluated
Agent
Claude Code
Model
Unknown

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.