agent-evaluator

Evaluate user queries against subagents and output a JSON decision payload.

5|Updated Dec 9, 2025
One-click install
npx skills add https://github.com/arisng/github-copilot-fc --skill agent-evaluator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-evaluator
Source: https://github.com/arisng/github-copilot-fc/tree/main/skills/agent-evaluator
Command: npx skills add https://github.com/arisng/github-copilot-fc --skill agent-evaluator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill provides a deterministic evaluator to decide which subagents to activate for a given user query, ensuring reproducible and auditable agent activation and a JSON decision payload.

Core Features & Use Cases

  • Deterministic evaluation of a user query against available subagents and generation of a JSON payload containing activated, required, and suggested agents.
  • Context-aware scoring using keyword signals, intent patterns, and optional file-context to influence activation decisions.
  • Use Case: Orchestrating a multi-agent workflow, run the evaluator to determine which subagents to activate and how to report results to downstream systems.

Quick Start

Run the evaluator on a user query to determine activation: python scripts/agent_evaluator.py 'create a flowchart'

Frequently Asked Questions about agent-evaluator

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

FAQPage Schema
How do I determine which subagents to activate in a multi-agent workflow?▼

To determine subagent activation, you can run an evaluator script against a user query to produce a deterministic JSON decision payload containing activated, required, and suggested agents.

What is deterministic subagent selection for auditable AI workflows?▼

Deterministic subagent selection evaluates user queries against available agents using keyword and intent matching, yielding a reproducible JSON payload with per-agent evaluations for auditing.

Can I use file context to influence subagent activation decisions?▼

Yes, the evaluator supports optional file context alongside keyword signals and intent patterns to provide context-aware scoring that influences subagent activation decisions.

How do I generate a JSON payload for orchestrating multi-agent workflows?▼

You can generate a JSON payload by executing the evaluation script with a user query, which outputs structured results including activated_agents, required_agents, and suggested_agents.

Why does my multi-agent workflow need a deterministic evaluator?▼

A deterministic evaluator ensures reproducible and auditable agent activation by replacing dynamic selection with structured per-agent evaluations, making downstream reporting consistent.