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Command

/eval

Evaluate a plugin or skill for quality

From plugin
wshobson-agents
39k95 skills139 agents95 commands
Install
$ npx -y skills add wshobson/agents --agent claude-code

How it fires

How this command gets triggered: by you, by Claude, or both.

  • Fires itselfClaude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/eval

Context preview

What this command does when you run it.

Evaluate a plugin or skill for quality

Command definition

eval.md
description: Evaluate a plugin or skill for quality
argument-hint: <path> [--depth quick|standard]

Run the PluginEval quality evaluation on a plugin or skill directory.

Usage

/eval <path> — evaluate at standard depth (static + LLM judge) /eval <path> --depth quick — static analysis only (instant)

Process

Step 1: Run Static Analysis (Layer 1)

cd "${CLAUDE_PLUGIN_ROOT}"
uv run plugin-eval score {argument} --depth quick --output json

Parse the JSON output to get `composite.score`, `composite.dimensions`, and `layers[0].anti_patterns`.

Step 2: LLM Judge (Layer 2) — if NOT --depth quick

Dispatch the `eval-judge` agent with the skill path:

> Evaluate the skill at: {resolved_path} > Read the SKILL.md file and any references/ files, then score it on all 4 dimensions. > Return your scores as JSON.

The judge returns scores for: triggering_accuracy, orchestration_fitness, output_quality, scope_calibration.

Step 3: Compute Final Score

**If quick depth:** Report the Layer 1 results directly from the CLI output.

**If standard depth:** Blend Layer 1 and Layer 2 scores.

For each dimension, use these blend weights (Static:Judge):

  • triggering_accuracy: 0.375:0.625
  • orchestration_fitness: 0.125:0.875
  • output_quality: 0.0:1.0 (judge only)
  • scope_calibration: 0.353:0.647
  • progressive_disclosure: 1.0:0.0 (static only)
  • token_efficiency: 0.8:0.2
  • robustness: 0.0:1.0 (judge only)
  • structural_completeness: 0.9:0.1
  • code_template_quality: 0.3:0.7
  • ecosystem_coherence: 0.85:0.15

Dimension weights: triggering(0.25), orchestration(0.20), output(0.15), scope(0.12), disclosure(0.10), efficiency(0.06), robustness(0.05), structural(0.03), code_quality(0.02), coherence(0.02)

Final = sum(weight * blended_score) * 100 * anti_pattern_penalty

Step 4: Present Results

## Overall Score: {score}/100 {badge}
## Layer Breakdown
| Layer | Score |
|-------|-------|
## Dimension Scores
| Dimension | Weight | Score | Grade |
|-----------|--------|-------|-------|
## Anti-Patterns Detected
## Recommendations

Badge thresholds: Platinum(90+), Gold(80+), Silver(70+), Bronze(60+)

Read more
Ships withwshobson-agents

Production-ready agentic workflow building blocks: 94 plugins, 203 agents, 175 skills, 109 commands — built for Claude Code and consumed natively by OpenAI Codex CLI, Cursor, OpenCode, Gemini CLI, and GitHub Copilot from a single Markdown source.

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Python
Language
MIT
License
3d ago
Last commit
1y ago
Created

Repo: wshobson/agents