Agent Evaluator

SkillAI & models

Deterministic custom subagent selection helper. Use when you need a reproducible, auditable decision on which custom subagents to activate for a user query (runs scripts/agent_evaluator.py).

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Agent Evaluator skill

What this skill tells your AI

The instructions your AI receives, as published by diegosouzapw/awesome-omni-skill in skills/data-ai/agent-evaluator/SKILL.md and read by ahel’s review.

Evaluate a user query against the workspace's available subagents and return a JSON decision payload (activated/required/suggested agents and scoring).

Mechanism

Run the evaluator script (located in scripts folder relative this skill file) with the user query as an argument.:

python scripts/agent_evaluator.py "YOUR_QUERY_HERE"

Optional: include a contextual file path as the second argument:

python scripts/agent_evaluator.py "YOUR_QUERY_HERE" "path/to/file.ext"

Output

  • Writes a JSON object to stdout.
  • Key fields include:
    • activated_agents
    • required_agents
    • suggested_agents
    • evaluations (per-agent score + reasoning)

Examples

Evaluate a query:

python scripts/agent_evaluator.py "Please help refine our custom instruction file"

Evaluate a query with file context:

python scripts/agent_evaluator.py "Update this instruction" "instructions/agent-forced-eval.instructions.md"

Signals

GitHub stars
57
Forks
19
Last commit
Mar 2026
Advanced
Catalog kind
skill
Gateway key
agent-evaluator-diegosouzapw
Source
github.com/diegosouzapw/awesome-omni-skill