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agent-performance-optimizer

Agent skill for performance-optimizer - invoke with $agent-performance-optimizer

Install with Tessl CLI

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

44

19.39x

Does it follow best practices?

Evaluation97%

19.39x

Agent success when using this skill

Validation for skill structure

SKILL.md
Review
Evals

Evaluation results

100%

100%

Compute Cluster Resource Allocation Optimizer

Sublinear solver resource allocation parameters

Criteria
Without context
With context

Uses solve tool

0%

100%

Solve method: neumann

0%

100%

Solve epsilon 1e-8

0%

100%

Solve maxIterations 1000

0%

100%

Matrix format field

0%

100%

Matrix rows/cols fields

0%

100%

Uses analyzeMatrix tool

0%

100%

checkDominance: true

0%

100%

estimateCondition: true

0%

100%

computeGap: true

0%

100%

Matrix and vector passed

0%

100%

Without context: $0.4429 · 1m 38s · 16 turns · 1,693 in / 5,759 out tokens

With context: $0.5134 · 2m 8s · 22 turns · 139 in / 7,495 out tokens

100%

97%

Distributed System Bottleneck Analyzer and Load Balancer

Bottleneck estimation and optimization validation

Criteria
Without context
With context

Uses estimateEntry tool

0%

100%

estimateEntry method: random-walk

0%

100%

estimateEntry epsilon 1e-6

0%

100%

estimateEntry confidence 0.95

0%

100%

Parallel estimation with Promise.all

33%

100%

Uses validateTemporalAdvantage

0%

100%

validateTemporalAdvantage distanceKm 1000

0%

100%

validateTemporalAdvantage size param

0%

100%

Load balance solve method: random-walk

0%

100%

Load balance epsilon 1e-6

0%

100%

Load balance maxIterations 500

0%

100%

Without context: $0.9851 · 5m 17s · 27 turns · 34 in / 19,743 out tokens

With context: $0.4640 · 1m 59s · 18 turns · 269 in / 7,109 out tokens

92%

80%

Real-Time Cloud Performance Monitoring and Prediction System

Flow Nexus sandbox configuration and neural training

Criteria
Without context
With context

Uses sandbox_create tool

0%

100%

Template: python

0%

100%

OPTIMIZATION_MODE env var

0%

100%

MONITORING_INTERVAL env var

0%

0%

RESOURCE_THRESHOLD env var

0%

100%

Required packages

50%

100%

Uses sandbox_execute with language python

0%

100%

80% threshold trigger

71%

100%

Uses neural_train tool

0%

100%

LSTM architecture

0%

100%

Dropout layer

0%

100%

Training hyperparameters

37%

100%

Tier medium

0%

100%

Without context: $0.5098 · 2m 52s · 21 turns · 26 in / 10,618 out tokens

With context: $0.4562 · 1m 59s · 20 turns · 273 in / 6,269 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.