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Skills/ruvnet/ruflo/worker-integration
worker-integration logo

worker-integration

ruvnet/ruflo
713 installs59K stars
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Installation

npx skills add https://github.com/ruvnet/ruflo --skill worker-integration

Summary

Worker-Agent integration for intelligent task dispatch and performance tracking

SKILL.md

Worker-Agent Integration Skill

Intelligent coordination between background workers and specialized agents.

Quick Start

# View agent recommendations for a trigger
npx agentic-flow workers agents ultralearn
npx agentic-flow workers agents optimize

# View performance metrics
npx agentic-flow workers metrics

# View integration stats
npx agentic-flow workers stats --integration

Agent Mappings

Workers automatically dispatch to optimal agents based on trigger type:

TriggerPrimary AgentsFallbackPipeline Phases
ultralearnresearcher, coderplannerdiscovery → patterns → vectorization → summary
optimizeperformance-analyzer, coderresearcherstatic-analysis → performance → patterns
auditsecurity-analyst, testerreviewersecurity → secrets → vulnerability-scan
benchmarkperformance-analyzercoder, testerperformance → metrics → report
testgapstestercoderdiscovery → coverage → gaps
documentdocumenter, researchercoderapi-discovery → patterns → indexing
deepdiveresearcher, security-analystcodercall-graph → deps → trace
refactorcoder, reviewerresearchercomplexity → smells → patterns

Performance-Based Selection

The system learns from execution history to improve agent selection:

// Agent selection considers:
// 1. Quality score (0-1)
// 2. Success rate
// 3. Average latency
// 4. Execution count

const { agent, confidence, reasoning } = selectBestAgent('optimize');
// agent: "performance-analyzer"
// confidence: 0.87
// reasoning: "Selected based on 45 executions with 94.2% success"

Memory Key Patterns

Workers store results using consistent patterns:

{trigger}/{topic}/{phase}

Examples:
- ultralearn$auth-module$analysis
- optimize$database$performance
- audit$payment$vulnerabilities
- benchmark$api$metrics

Benchmark Thresholds

Agents are monitored against performance thresholds:

{
  "researcher": {
    "p95_latency": "<500ms",
    "memory_mb": "<256MB"
  },
  "coder": {
    "p95_latency": "<300ms",
    "quality_score": ">0.85"
  },
  "security-analyst": {
    "scan_coverage": ">95%",
    "p95_latency": "<1000ms"
  }
}

Feedback Loop

Workers provide feedback for continuous improvement:

import { workerAgentIntegration } from 'agentic-flow$workers$worker-agent-integration';

// Record execution feedback
workerAgentIntegration.recordFeedback(
  'optimize',           // trigger
  'coder',              // agent
  true,                 // success
  245,                  // latency ms
  0.92                  // quality score
);

// Check compliance
const { compliant, violations } = workerAgentIntegration.checkBenchmarkCompliance('coder');

Integration Statistics

$ npx agentic-flow workers stats --integration

Worker-Agent Integration Stats
══════════════════════════════
Total Agents:       6
Tracked Agents:     4
Total Feedback:     156
Avg Quality Score:  0.89

Model Cache Stats
─────────────────
Hits:     1,234
Misses:   45
Hit Rate: 96.5%

Configuration

Enable integration features in .claude$settings.json:

{
  "workers": {
    "enabled": true,
    "parallel": true,
    "memoryDepositEnabled": true,
    "agentMappings": {
      "ultralearn": ["researcher", "coder"],
      "optimize": ["performance-analyzer", "coder"]
    }
  }
}

Score

0–100
65/ 100

Grade

C

Popularity17/30

713 installs — growing adoption. Source repo has 59,493 GitHub stars.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Worker Integration skill score badge previewScore badge

Markdown

[![Worker Integration skill](https://www.claudemarket.ai/skills/ruvnet/ruflo/worker-integration/badges/score.svg)](https://www.claudemarket.ai/skills/ruvnet/ruflo/worker-integration)

HTML

<a href="https://www.claudemarket.ai/skills/ruvnet/ruflo/worker-integration"><img src="https://www.claudemarket.ai/skills/ruvnet/ruflo/worker-integration/badges/score.svg" alt="Worker Integration skill"/></a>

Worker Integration FAQ

How do I install the Worker Integration skill?

Run “npx skills add https://github.com/ruvnet/ruflo --skill worker-integration” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Worker Integration skill do?

Worker-Agent integration for intelligent task dispatch and performance tracking The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Worker Integration skill free?

Yes. Worker Integration is a free, open-source skill published from ruvnet/ruflo. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Worker Integration work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Worker Integration works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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