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skill-grader技能分级员

Agent Skill

skill-grader 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,533

周安装

62

GitHub Stars

98

下载量

481
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:skill-grader(技能分级员)
来源仓库:https://github.com/erichowens/some_claude_skills
仓库路径:skills/skill-grader
安装命令:
npx skills add https://github.com/erichowens/some_claude_skills --skill skill-grader
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/erichowens/some_claude_skills --skill skill-grader

简介

为 Claude Agent 技能提供结构化评估量表和字母等级评定。

  • 从十个维度进行质量审计,给出具体改进建议和优先级排序。
  • 适用于非专家用户对技能库进行质量控制和质量改进规划。skill-grader 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 产出 A+ 到 F 等级评分和改进路线图,便于技能迭代管理。
  • 使用时需配合原始 README 内容交叉验证评估结果的准确性。

SKILL.md

Skill Grader

Structured evaluation rubric for Claude Agent Skills. Produces letter grades (A+ through F) on 10 axes plus an overall grade, with specific improvement recommendations for each axis.

Designed for sub-agents and non-expert reviewers who need a mechanical, repeatable process for assessing skill quality without deep domain expertise.


When to Use

Use for:

  • Auditing a single skill's quality
  • Comparing skills against each other
  • Prioritizing which skills to improve first
  • Quality control sweeps across a skill library
  • Generating improvement roadmaps

NOT for:

  • Creating new skills (use skill-architect)
  • Grading code quality or non-skill documents
  • Evaluating agent performance (different from skill quality)

Grading Process

flowchart TD
  A[Read SKILL.md + all files] --> B[Score each of 10 axes]
  B --> C[Assign letter grade per axis]
  C --> D[Compute overall grade]
  D --> E[Write improvement recommendations]
  E --> F[Produce grading report]

Step-by-Step

  1. Read the entire skill folder — SKILL.md, all references, scripts, CHANGELOG, README
  2. Score each axis — Use the rubric below (0-100 per axis)
  3. Convert to letter grade — See grade scale
  4. Compute overall grade — Weighted average (Description and Scope are 2x weight)
  5. Write 1-3 specific improvements per axis scoring below B+
  6. Produce the grading report in the output format below

The 10 Evaluation Axes

Axis 1: Description Quality (Weight: 2x)

Does the description follow [What] [When] [Keywords]. NOT for [Exclusions]?

GradeCriteria
ASpecific verb+noun, domain keywords users would type, 2-5 explicit NOT exclusions, 25-50 words
BHas keywords and NOT clause, but slightly vague or missing synonym coverage
CToo generic, missing NOT clause, or >100 words of process detail
DSingle vague sentence ("helps with X") or name/description mismatch
FMissing or empty description

Axis 2: Scope Discipline (Weight: 2x)

Is the skill narrowly focused on one expertise type, or a catch-all?

GradeCriteria
AOne clear expertise domain, "When to Use" and "NOT for" sections both present and specific
BMostly focused, minor boundary ambiguity
CCovers 2-3 related but distinct domains, should probably be split
DCatch-all skill ("helps with anything related to X")
FNo scope boundaries defined at all

Axis 3: Progressive Disclosure

Does the skill follow the three-layer architecture (metadata → SKILL.md → references)?

GradeCriteria
ASKILL.md <300 lines, heavy content in references, reference index in SKILL.md with 1-line descriptions
BSKILL.md <500 lines, some references used, index present
CSKILL.md >500 lines, or all content inlined with no references
DSKILL.md >800 lines, or references exist but aren't indexed in SKILL.md
FSingle massive file with no structure

Axis 4: Anti-Pattern Coverage

Does the skill encode expert knowledge that prevents common mistakes?

GradeCriteria
A3+ anti-patterns with Novice/Expert/Timeline template, LLM-mistake notes
B1-2 anti-patterns with clear explanation
CAnti-patterns mentioned but no structured template
DNo anti-patterns, just positive instructions
FContains advice that IS an anti-pattern (outdated, harmful)

Axis 5: Self-Contained Tools

Does the skill include working tools (scripts, MCPs, subagents)?

GradeCriteria
AWorking scripts with CLI interface, error handling, dependency docs; OR valid "no tools needed" justification
BScripts exist and work but lack error handling or docs
CScripts referenced but are templates/pseudocode
DPhantom tools (SKILL.md references files that don't exist)
FReferences non-existent tools AND no acknowledgment

Note: Not every skill needs tools. A pure decision-tree skill can score A if tools aren't applicable.

Axis 6: Activation Precision

Would the skill activate correctly on relevant queries and stay silent on irrelevant ones?

GradeCriteria
ADescription has specific keywords matching user language, clear NOT clause, no obvious false-positive vectors
BGood keywords, minor false-positive risk
CGeneric keywords that overlap with other skills
DNo specific keywords, or NOT clause contradicts intended use
FDescription would cause constant false activation

Axis 7: Visual Artifacts

Does the skill use Mermaid diagrams, code examples, and tables effectively?

GradeCriteria
ADecision trees as Mermaid flowcharts, tables for comparisons, code examples for concrete patterns
BSome diagrams or tables, but key decision trees still in prose
CTables used but no Mermaid diagrams for processes
DProse-only, no visual structure
FWall of text with no formatting aids

Axis 8: Output Contracts

Does the skill define what it produces in a format consumable by other agents?

GradeCriteria
AExplicit output format (JSON schema, markdown template, or structured sections), subagent-consumable
BOutput format implied but not explicitly documented
CNo output format, but content is structured enough to infer
DUnstructured prose output expected
FN/A (pure reference skill) — exempt from this axis

Axis 9: Temporal Awareness

Does the skill track when knowledge was current and what has changed?

GradeCriteria
ATimelines in anti-patterns, "as of [date]" markers, CHANGELOG with dates
BSome temporal context, CHANGELOG exists
CNo dates on knowledge, but CHANGELOG exists
DNo temporal context anywhere, knowledge could be stale
FContains demonstrably outdated advice without warning

Axis 10: Documentation Quality

README, CHANGELOG, and reference organization.

GradeCriteria
AREADME with quick start, CHANGELOG with dated versions, references well-organized with clear filenames
BREADME and CHANGELOG exist, references present
CSKILL.md is the only file, but it's well-structured
DNo README, no CHANGELOG, disorganized references
FSKILL.md is the only file and it's poorly structured

Grade Scale

LetterScore RangeMeaning
A+97-100Exemplary — sets the standard
A93-96Excellent — minor improvements possible
A-90-92Very good — a few small gaps
B+87-89Good — notable room for improvement
B83-86Solid — several areas need work
B-80-82Above average — meaningful gaps
C+77-79Average — significant improvements needed
C73-76Below average — major gaps
C-70-72Barely adequate
D+67-69Poor — fundamental issues
D63-66Very poor — needs major rework
D-60-62Near-failing quality
F<60Failing — start over

Overall Grade Computation

Axes 1 (Description) and 2 (Scope) carry 2x weight. All others carry 1x weight. If Axis 8 (Output Contracts) is marked exempt, remove it from the calculation.

Overall = (2×Axis1 + 2×Axis2 + Axis3 + Axis4 + Axis5 + Axis6 + Axis7 + Axis8 + Axis9 + Axis10) / 12

Convert the numeric average to a letter grade using the scale above.


Output Format

Produce this exact structure:

# Skill Grading Report: [skill-name]

**Graded**: [date]
**Overall Grade**: [letter] ([score]/100)

## Axis Grades

| # | Axis | Grade | Score | Key Finding |
|---|------|-------|-------|-------------|
| 1 | Description Quality | [grade] | [score] | [1-line finding] |
| 2 | Scope Discipline | [grade] | [score] | [1-line finding] |
| 3 | Progressive Disclosure | [grade] | [score] | [1-line finding] |
| 4 | Anti-Pattern Coverage | [grade] | [score] | [1-line finding] |
| 5 | Self-Contained Tools | [grade] | [score] | [1-line finding] |
| 6 | Activation Precision | [grade] | [score] | [1-line finding] |
| 7 | Visual Artifacts | [grade] | [score] | [1-line finding] |
| 8 | Output Contracts | [grade] | [score] | [1-line finding] |
| 9 | Temporal Awareness | [grade] | [score] | [1-line finding] |
| 10 | Documentation Quality | [grade] | [score] | [1-line finding] |

## Top 3 Improvements (Highest Impact)

1. **[Axis]: [Specific action]** — [Why this matters, expected grade improvement]
2. **[Axis]: [Specific action]** — [Why this matters, expected grade improvement]
3. **[Axis]: [Specific action]** — [Why this matters, expected grade improvement]

## Detailed Notes

### [Axis name] ([grade])
[2-3 sentences of specific feedback with examples from the skill]

[Repeat for each axis scoring below B+]

Quick Grading (Abbreviated)

For rapid triage across many skills, produce only:

| Skill | Overall | Desc | Scope | Disc | Anti | Tools | Activ | Visual | Output | Temp | Docs |
|-------|---------|------|-------|------|------|-------|-------|--------|--------|------|------|
| [name] | [grade] | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |

Anti-Patterns in Grading

Grade Inflation

Wrong: Giving B+ because "it's pretty good" without checking criteria. Right: Match observations to the rubric table literally. If the description lacks a NOT clause, it cannot score above C on Axis 1.

Missing Context

Wrong: Grading a pure decision-tree skill poorly on Axis 5 (tools) because it has no scripts. Right: Mark Axis 5 as "A — tools not applicable for this skill type."

Ignoring Phantoms

Wrong: Scoring Axis 5 as B because scripts are "referenced." Right: Actually check if every referenced file exists. If scripts/validate.py is mentioned but doesn't exist, that's D.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.63%
按下载量换算186

Claude

31.01%
按下载量换算149

Cursor

18.21%
按下载量换算88

Gemini CLI

9.93%
按下载量换算48

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills