Skill Scorer

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📚 知识管理 免费

📖 技能介绍

Skill: skill-scorer

Overview

A meta-skill that evaluates the quality of other skills. Given a SKILL.md file (or a complete skill folder), it performs a systematic audit across 8 dimensions, assigns a score out of 100, identifies issues by severity, and generates actionable optimization suggestions.

This skill synthesizes quality criteria from Anthropic's official skill authoring best practices, the Skill Engineering Standard (v1.4.3), and community-tested patterns from production skill ecosystems.

When to Activate

User provides a skill and asks any of:

  • "帮我评分/打分/检测/质检 这个 skill"
  • "review/audit/score/grade/lint this skill"
  • "这个 skill 写得怎么样?" / "is this skill any good?"
  • "帮我优化这个 skill" (evaluate first, then suggest improvements)
  • Provides a SKILL.md and expects quality feedback

Do NOT activate for: creating a new skill from scratch → use skill-creator. This skill is for evaluation, not generation.

Core Workflow

Step 0: Load the Skill Under Test

Determine what the user has provided:

Input Action
Single SKILL.md file Evaluate that file
Skill folder (with references/) Evaluate all files, cross-reference consistency
URL / GitHub link Fetch and evaluate
Pasted markdown content Treat as SKILL.md

If the user has not provided a skill → ask: "请提供要评估的 SKILL.md 文件或 skill 文件夹路径。"

Input validation — before proceeding to Step 1, verify the input is actually a skill:

Check Condition Action
Binary / garbled content File is not valid text, or text is unreadable gibberish STOP. Report: "This file does not appear to be a valid SKILL.md — it contains binary or unreadable content. Please provide a markdown-based skill file." Do NOT attempt to score.
No skill markers at all Text is valid but contains zero skill indicators (no YAML frontmatter ---, no markdown headings resembling skill sections, no workflow/instructions) STOP. Report: "This appears to be a {detected_type} file (e.g., Python script, JSON config, plain prose), not a SKILL.md. skill-scorer evaluates SKILL.md files only." Do NOT force-fit 8 dimensions onto non-skill content.
Partial skill structure Has some skill-like elements (e.g., YAML frontmatter exists but body is minimal, or has headings but no workflow) PROCEED with caveats. Evaluate normally, but note in the report header: "⚠️ This file has incomplete skill structure — scores reflect what is present." Score missing sections as 0 in relevant dimensions rather than guessing.

Step 1: Parse Skill Structure

Extract and inventory:

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  • YAML frontmatter fields (name, description, version, compatibility)
  • Section headings and their order
  • References to external files (references/, scripts/, assets/)
  • Total line count and estimated token count of SKILL.md body

Step 2: Run 8-Dimension Evaluation

Read references/rubric.md for the complete scoring rubric.

Evaluate the skill across these 8 dimensions (each scored 0-100, then weighted):

# Dimension Weight What It Measures
1 Metadata & Triggering 15% Name clarity, description quality, trigger coverage
2 Structure & Architecture 15% File organization, section order, progressive disclosure
3 Instruction Clarity 15% Actionability, conciseness, examples, tone
4 Workflow & Logic 15% Step completeness, parameter handling, validation
5 Error Handling 10% Fallbacks, edge cases, failure recovery
6 Context Efficiency 10% Token budget, redundancy, information density
7 Portability & Compatibility 10% Self-containment, cross-platform support
8 Safety & Robustness 10% No injection risk, no hallucination traps, identity lock

Step 3: Identify Issues

For each issue found, classify severity:

Severity Meaning Score Impact
🔴 Critical Skill will malfunction or not trigger -10 to -15 per issue
🟡 Warning Skill works but suboptimally -3 to -8 per issue
🟢 Suggestion Nice-to-have improvement -1 to -2 per issue

Step 4: Generate Report

Read references/report-template.md for the output format.

The report includes:

  1. Score Card — Overall score + per-dimension breakdown
  2. Issue List — All findings sorted by severity
  3. Top 3 Quick Wins — Highest-impact fixes with before/after examples
  4. Optimization Roadmap — Prioritized improvement plan

Step 5: Offer Follow-Up

After presenting the report, ask:

  • "需要我帮你自动修复这些问题吗?" (auto-fix mode)
  • "需要对某个维度深入分析吗?" (deep-dive mode)
  • "需要生成优化后的 SKILL.md 吗?" (rewrite mode)

Output Rules

  1. Bilingual report — Chinese first, English after, no interleaving. Always output the complete report in Chinese, then a --- separator, then the complete report in English. Never mix languages within a section. Both versions must contain identical scores, issues, and suggestions — only the language differs.
  2. Score must be justified. Every deducted point must trace to a specific issue.
  3. Suggestions must be actionable. Include before/after code snippets, not vague advice.
  4. Be constructive, not destructive. Lead with what the skill does well before listing issues.
  5. ❌ Never inflate scores to be polite — honest assessment helps the user improve.
  6. ❌ Never evaluate based on domain correctness of the skill's content (e.g., whether hotel recommendations are good) — only evaluate skill engineering quality.

References

File Purpose When to read
references/rubric.md Detailed scoring criteria for all 8 dimensions Step 2: scoring
references/report-template.md Output format and report structure Step 4: generating report
references/anti-patterns.md Common skill mistakes and how to detect them Step 3: finding issues

🤖 AI 评测

这个 Skill 质量很高,设计专业、结构清晰,能对其他 Skill 进行全面系统的质量评估,评分标准细致,反模式检测全面。双语支持完善,文档组织有序。优点是架构设计合理、验证逻辑健全、版本管理规范;小瑕疵是部分参考文档可能被截断、缺少快速示例。总体是一款优秀的质量评估工具。

📊 多维度评分

适应性4.8
规范性4.8
有效性4.6
可靠性4.5
可信度5

📁 包含文件 (6 个)

📄 README.md 7.3 KB
📄 SKILL.md 8 KB
📄 _meta.json 131 B
📄 references/anti-patterns.md 11.3 KB
📄 references/report-template.md 7.9 KB
📄 references/rubric.md 20.9 KB