worker-integration

Name: worker-integration
Availability: InStock
Author: joeyjoziah

Route worker-triggered tasks to specialized agents using performance metrics.

Updated Aug 13, 2025

Search Tags:#workflow orchestration #agent selection #feedback loop #performance tracking #memory coordination #task routing #worker-agent

Ready to run

npx skills add https://github.com/JoeyJoziah/investment-analysis-platform --skill worker-integration-joeyjoziah

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: worker-integration
Source: https://github.com/JoeyJoziah/investment-analysis-platform/tree/main/.claude/skills
Command: npx skills add https://github.com/JoeyJoziah/investment-analysis-platform --skill worker-integration-joeyjoziah

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the problem of manually deciding which worker or specialist agent should handle a task, reducing slow, inconsistent, or poorly routed execution.

Core Features & Use Cases

Trigger-Based Agent Selection: Maps task triggers such as ultralearn, optimize, audit, benchmark, testgaps, document, deepdive, and refactor to the best primary and fallback agents.
Performance Tracking: Records quality, success rate, latency, and execution count so routing decisions improve over time.
Memory Coordination: Stores outputs in consistent trigger/topic/phase keys to preserve context across pipelines and sessions.
Use Case: When a workflow needs the best agent for optimization, auditing, benchmarking, or refactoring, this skill dispatches the job, captures feedback, and refines future selection.

Quick Start

Use the worker-integration skill to inspect a trigger, confirm the recommended agent, and review the related metrics before dispatching your task.

Frequently Asked Questions about worker-integration

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is workflow orchestration for agent selection?▼

Workflow orchestration for agent selection maps task triggers like optimize, audit, and refactor to the most suitable specialized agents, recording performance metrics to refine future routing decisions. It establishes feedback loops to continuously improve dispatch consistency.

How do I route tasks to specialized agents automatically?▼

To route tasks automatically, you inspect the task trigger, confirm the recommended primary and fallback agents, review historical execution metrics, and dispatch the job to capture performance feedback for future routing.

Can I use worker-agent routing for benchmark and refactor workflows?▼

Yes, worker-agent routing supports benchmark and refactor workflows by applying consistent pipeline phases, memory key conventions, and handoff coordination to ensure specialized agents execute tasks correctly.

What's the best way to track agent performance in pipeline orchestration?▼

The best way to track agent performance in pipeline orchestration is to record quality, success rate, latency, and execution count, using these metrics as benchmark thresholds to optimize routing and track compliance.

How does memory coordination work across pipeline phases?▼

Memory coordination stores outputs in consistent trigger, topic, and phase keys, preserving context across pipelines and sessions so that specialized agents maintain execution history and routing consistency.

Do I need benchmark thresholds to optimize task routing?▼

Yes, benchmark thresholds are required alongside performance scoring, execution history, memory key conventions, and feedback loops to optimize routing decisions and track compliance across worker-triggered tasks.