metric-pack-designer

Design custom metric packs that emit schema-compatible checks and metrics for plugin-eval.

5.3k|765|Updated Mar 4, 2026
One-click install
npx skills add https://github.com/openai/plugins --skill metric-pack-designer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: metric-pack-designer
Source: https://github.com/openai/plugins/tree/main/plugins/plugin-eval/skills/metric-pack-designer
Command: npx skills add https://github.com/openai/plugins --skill metric-pack-designer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Teams using plugin-eval often need evaluation criteria beyond the built-in rubric, but writing schema-compatible custom checks and metrics from scratch is error-prone. This Skill guides the creation of local metric packs that integrate cleanly with the plugin-eval analysis pipeline.

Core Features & Use Cases

  • Custom Rubric Design: Clarify rubric categories and target kinds, then define the smallest useful checks[] and metrics[] payload.
  • Manifest and Script Generation: Create a metric-pack manifest plus a script that prints JSON to stdout for deterministic evaluation.
  • Stable, Comparable Output: Keep IDs stable across runs and emit only checks[], metrics[], and optional artifacts[] without overwriting the core score.
  • Use Case: A team wants to enforce internal code-quality rules during plugin evaluation. Use this Skill to build a local metric pack, then run it via plugin-eval analyze with the --metric-pack flag.

Quick Start

Design a custom metric pack for plugin-eval that checks my plugin for our team's naming conventions and emits schema-compatible metrics.

Frequently Asked Questions about metric-pack-designer

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

FAQPage Schema
How do I create a custom metric pack for plugin-eval?

Define your rubric categories and target kinds, then create a manifest plus a script that prints JSON to stdout containing checks[] and metrics[] arrays. Run it with plugin-eval analyze <path> --metric-pack <manifest.json> to apply your custom criteria.

What output format does a plugin-eval metric pack require?

A metric pack script must print JSON to stdout containing only checks[], metrics[], and optional artifacts[] arrays. It must not attempt to overwrite the core score or summary produced by plugin-eval.

Can a custom metric pack override the plugin-eval core score?

No, custom metric packs cannot overwrite the core score or summary. They only contribute additional checks and metrics alongside the built-in evaluation results.

Why should metric pack check IDs stay stable across runs?

Stable IDs keep results comparable between runs, so trends and regressions remain meaningful. Changing IDs breaks historical comparisons and makes it impossible to track whether a check improved or degraded over time.

When should I use deterministic signals instead of text generation in a metric pack?

Prefer deterministic local signals whenever possible because they produce reproducible, comparable results across runs. Subjective text generation introduces variance that undermines the reliability of your evaluation metrics.