CatalogOpenAI Codex Plugins · OpenAI

evaluate-plugin

Evaluate a local Codex plugin in engineer-friendly language. Use when the user says "evaluate this plugin", "audit this plugin", "why did this score that way", "what should I fix first", "help me benchmark this plugin", or asks for a plugin-wide report before comparing versions.

AnalyzedOfficial7.5k stars

Savant verdict: Analyzed

Scanned or evaluated by Savant; not yet both passing.

Live evaluation

Not evaluated yet. Workspaces can request a live evaluation.

Safety (NVIDIA SkillSpector)

Risk score
0/100
Recommendation
CAUTION
Severity
LOW
Savant decision
Passed (low risk)
SkillSpector rated it CAUTION, but its risk score is below 20/100, so Savant's policy passes it. Its findings are still listed for review. SkillSpector 2.12.0, static analysis.

0 patterns found

Structure

  • No license declaredConfirm you may reuse this skill before importing it into your repository.

SKILL.md

---
name: evaluate-plugin
description: Evaluate a local Codex plugin in engineer-friendly language. Use when the user says "evaluate this plugin", "audit this plugin", "why did this score that way", "what should I fix first", "help me benchmark this plugin", or asks for a plugin-wide report before comparing versions.
---

# Evaluate Plugin

Use this skill when the target is a plugin root with `.codex-plugin/plugin.json`.

## Workflow

1. Treat "Evaluate this plugin." as the default entrypoint.
2. If the request comes in as natural chat language, use `plugin-eval start <plugin-root> --request "<user request>" --format markdown` first so the user sees the routed local path.
3. Run `plugin-eval analyze <plugin-root> --format markdown`.
4. Read `Fix First` before drilling into manifest findings, nested skill findings, and code or coverage details.
5. If the plugin contains multiple skills, summarize the strongest and weakest ones explicitly.
6. If the user wants measured usage, switch to "Help me benchmark this plugin." and use the starter benchmark flow.
7. If the user wants trend data, compare two JSON outputs with `plugin-eval compare`.

## Chat Requests To Recognize

- `Evaluate this plugin.`
- `Audit this plugin.`
- `Why did this score that way?`
- `What should I fix first?`
- `Help me benchmark this plugin.`
- `What should I run next?`

## Commands

```bash
plugin-eval start <plugin-root> --request "Evaluate this plugin." --format markdown
plugin-eval analyze <plugin-root> --format markdown
plugin-eval start <plugin-root> --request "What should I run next?" --format markdown
plugin-eval compare before.json after.json
plugin-eval report result.json --format html --output ./plugin-eval-report.html
plugin-eval init-benchmark <plugin-root>
plugin-eval benchmark <plugin-root> --dry-run
```

## Reference

- `../../references/chat-first-workflows.md`