skill-comparator

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Chinese

Skill Comparator

Skill 比较器

Fetch the skill, read it deeply, evaluate it across 10 dimensions, compare against requirements or an alternative, produce a structured report.
Core principle: Never summarize shallowly. Read the actual skill content. Quote specific lines as evidence. Every score must have a justification.

获取Skill内容,深度解读,从10个维度进行评估,与需求或替代方案对比,生成结构化报告。
核心原则: 切勿浅层次总结。务必阅读Skill的实际内容。引用具体内容作为证据。每一项评分都必须有依据。

PHASE 1 — Skill Acquisition

阶段1 — Skill 获取

1.1 Determine Source

1.1 确定来源

Source types:
A) skills.sh URL      → https://skills.sh/author/skills/skillname
B) GitHub URL         → https://github.com/org/repo/blob/main/skill/SKILL.md
C) Raw GitHub URL     → https://raw.githubusercontent.com/...
D) Uploaded file      → User uploads SKILL.md directly
E) Local path         → /path/to/SKILL.md
F) Skill name only    → Search skills.sh first, then GitHub
Source types:
A) skills.sh URL      → https://skills.sh/author/skills/skillname
B) GitHub URL         → https://github.com/org/repo/blob/main/skill/SKILL.md
C) Raw GitHub URL     → https://raw.githubusercontent.com/...
D) Uploaded file      → User uploads SKILL.md directly
E) Local path         → /path/to/SKILL.md
F) Skill name only    → Search skills.sh first, then GitHub

1.2 Fetch Strategy

1.2 获取策略

For skills.sh URLs:
1. Fetch the page with web_fetch
2. Extract SKILL.md content from the page
3. Also extract metadata:
   - Weekly installs
   - Security audit results (Trust Hub / Socket / Audit)
   - First seen date
   - Supported platforms (claude-code, copilot, etc.)
   - Repository link
For GitHub URLs:
1. Convert to raw URL and attempt `web_fetch`.
2. If `web_fetch` fails (e.g., due to private repository authentication), do NOT give up immediately. Automatically attempt to use local Git tools (e.g., `git clone` to a temp directory, or GitHub CLI `gh api`).
3. Fetch raw SKILL.md content.
4. If all automated fetches fail or if instructed, ask the user to manually paste the SKILL.md content as a fallback.
For uploaded files:
Read content directly — no fetch needed
针对skills.sh链接:
1. 使用web_fetch获取页面
2. 从页面中提取SKILL.md内容
3. 同时提取元数据:
   - 周安装量
   - 安全审计结果(Trust Hub / Socket / Audit)
   - 首次上线日期
   - 支持平台(claude-code、copilot等)
   - 仓库链接
针对GitHub链接:
1. 转换为原始链接并尝试使用`web_fetch`。
2. 如果`web_fetch`失败(例如因私有仓库认证问题),请勿立即放弃。自动尝试使用本地Git工具(例如`git clone`到临时目录,或GitHub CLI `gh api`)。
3. 获取原始SKILL.md内容。
4. 如果所有自动获取方式均失败或收到指示,请要求用户手动粘贴SKILL.md内容作为备选方案。
针对上传文件:
直接读取内容——无需获取操作

1.3 If Skill Cannot Be Fetched

1.3 若无法获取Skill内容

Inform the user:
"Could not fetch the skill at [URL].
Options:
1. Paste the SKILL.md content directly into the chat
2. Upload the SKILL.md file
3. Provide a different URL"

告知用户:
"无法获取链接[URL]对应的Skill内容。
可选方案:
1. 将SKILL.md内容直接粘贴到聊天框中
2. 上传SKILL.md文件
3. 提供其他链接"

PHASE 2 — Deep Reading

阶段2 — 深度解读

Before scoring, read the entire skill carefully. Extract and note:
□ Name and version
□ Language (English / Spanish / other)
□ Description / trigger conditions
□ Scope: what does it actually do?
□ Target project/context (general or specific to one project?)
□ Steps / phases / instructions
□ Config files or templates included
□ Hardcoded values (magic numbers, project-specific strings)
□ Security practices
□ Error handling
□ What it explicitly does NOT do
□ Dependencies mentioned
□ Output files / artifacts produced
□ Notes / warnings / caveats
Red flags to note immediately:
⚠️  Embedded plaintext credentials, auth tokens, project names
⚠️  Written in a language you don't understand
⚠️  "latest" image tags instead of pinned versions
⚠️  No error handling
⚠️  Scope too narrow (one project only)
⚠️  Last updated > 1 year ago
⚠️  Security audit failures (Scanner Flagged, etc.)

评分前,仔细阅读整个Skill内容。提取并记录:
□ 名称与版本
□ 语言(英语/西班牙语/其他)
□ 描述/触发条件
□ 范围:实际能完成什么?
□ 目标项目/场景(通用或特定于某个项目?)
□ 步骤/阶段/说明
□ 包含的配置文件或模板
□ 硬编码值(魔数、项目特定字符串)
□ 安全实践
□ 错误处理
□ 明确说明不支持的功能
□ 提及的依赖项
□ 生成的输出文件/产物
□ 注意事项/警告/提示
需立即记录的风险信号:
⚠️  嵌入明文凭证、认证令牌、项目名称
⚠️  使用你无法理解的语言编写
⚠️  使用"latest"镜像标签而非固定版本
⚠️  无错误处理机制
⚠️  范围过于狭窄(仅适用于一个项目)
⚠️  上次更新距今超过1年
⚠️  安全审计失败(如Scanner Flagged等)

PHASE 3 — 10-Dimension Scoring

阶段3 — 10维度评分

Score each RELEVANT dimension 1-10. Every score requires a one-line justification with a direct quote or reference from the skill content.
CRITICAL ADAPTIVE SCORING RULE: If a dimension (e.g., ORM Compatibility, Monitoring) is completely irrelevant to the skill being analyzed (e.g., a frontend UI checker that has no database), mark the score as
N/A
. DO NOT penalize the skill for irrelevant dimensions. Subtract that dimension's maximum points (10) from the total available points, and calculate the final percentage scaled out of the remaining valid dimensions (e.g., 72/80 = 90%).

为每个相关维度打分(1-10分)。每一项评分都需要结合Skill内容中的直接引用或参考给出一行依据。
关键自适应评分规则: 如果某个维度(例如ORM兼容性、监控)与当前分析的Skill完全无关(例如一个不涉及数据库的前端UI检查工具),则标记为
N/A
。切勿因无关维度对Skill扣分。将该维度的满分(10分)从总可用分数中扣除,并根据剩余有效维度计算最终百分比(例如72/80=90%)。

DIMENSION 1 — Scope & Generality (weight: high)

维度1 — 范围与通用性(权重:高)

1-3:  Written for a single specific project, hardcoded names/values
4-6:  Partially general but has project-specific assumptions
7-9:  General purpose, works across different projects
10:   Fully general, adapts to any context through discovery questions

Evidence: Quote any hardcoded project names, DB names, or fixed values

1-3分:为单个特定项目编写,包含硬编码名称/值
4-6分:部分通用,但存在项目特定假设
7-9分:通用型,可在不同项目中使用
10分:完全通用,通过探索性问题适配任意场景

证据:引用任何硬编码的项目名称、数据库名称或固定值

DIMENSION 2 — Technical Depth (weight: high)

维度2 — 技术深度(权重:高)

1-3:  Surface-level instructions, no formulas, no reasoning
4-6:  Some depth, covers common cases
7-9:  Deep coverage, explains WHY not just WHAT, handles edge cases
10:   Expert-level, includes formulas, calculations, trade-off analysis

Evidence: Note what's missing vs what's covered

1-3分:仅提供表面级说明,无公式、无推理
4-6分:具备一定深度,覆盖常见场景
7-9分:深度覆盖,解释原理而非仅操作步骤,处理边缘情况
10分:专家级,包含公式、计算、权衡分析

证据:记录缺失内容与覆盖内容的对比

DIMENSION 3 — Decision Intelligence (weight: high)

维度3 — 决策智能(权重:高)

1-3:  No decision making — just applies a fixed approach
4-6:  Some conditional logic ("if X then Y")
7-9:  Asks questions, analyzes context, selects best approach
10:   Full decision tree with justifications for each branch

Evidence: Quote any decision logic or lack thereof

1-3分:无决策逻辑——仅应用固定流程
4-6分:具备部分条件逻辑("如果X则Y")
7-9分:主动提问、分析场景、选择最优方案
10分:完整决策树,每个分支都有依据

证据:引用任何决策逻辑或说明其缺失情况

DIMENSION 4 — ORM / Framework Compatibility (weight: medium)

维度4 — ORM/框架兼容性(权重:中)

Skip or reduce weight if skill is not database/backend related
1-3:  Works with one specific ORM/framework only
4-6:  Covers 2-3 ORMs with basic notes
7-9:  Covers major ORMs with specific config for each
10:   Comprehensive matrix, edge cases, migration paths

Evidence: List which ORMs/frameworks are mentioned

若Skill与数据库/后端无关,可跳过或降低权重
1-3分:仅适用于一种特定ORM/框架
4-6分:覆盖2-3种ORM,附带基础说明
7-9分:覆盖主流ORM,每种都有特定配置说明
10分:包含全面兼容性矩阵、边缘情况处理、迁移路径

证据:列出提及的ORM/框架

DIMENSION 5 — Security Practices (weight: high)

维度5 — 安全实践(权重:高)

1-3:  Embedded plaintext secrets, no security considerations, Scanner Flagged
4-6:  Basic security (mentions env vars) but incomplete
7-9:  Proper secret handling, CVE awareness, security checklist
10:   Passes skill-security audit, no hardcoded values, CVE check included

Evidence: Quote any hardcoded values, auth_type, secret handling

1-3分:嵌入明文密钥,无安全考量,Scanner Flagged
4-6分:基础安全(提及环境变量)但不完善
7-9分:正确处理密钥,具备CVE意识,包含安全检查清单
10分:通过skill-security审计,无硬编码值,包含CVE检查

证据:引用任何硬编码值、auth_type、密钥处理方式

DIMENSION 6 — Output Quality (weight: medium)

维度6 — 输出质量(权重:中)

1-3:  No structured output, ad-hoc
4-6:  Some output but incomplete or unstructured
7-9:  Clear output files defined, structured format
10:   Multiple output artifacts, each with defined purpose and format

Evidence: List what outputs are produced

1-3分:无结构化输出,临时生成
4-6分:有部分输出但不完整或非结构化
7-9分:定义清晰的输出文件,格式结构化
10分:多种输出产物,每种都有明确用途和格式

证据:列出生成的输出内容

DIMENSION 7 — Error Handling (weight: medium)

维度7 — 错误处理(权重:中)

1-3:  No error handling, assumes everything works
4-6:  Mentions some failure modes
7-9:  Clear fallback paths, skip conditions, fail-open/fail-closed
10:   Comprehensive error taxonomy, recovery procedures, user communication

Evidence: Quote any error handling or note its absence

1-3分:无错误处理,假设所有操作均成功
4-6分:提及部分失败场景
7-9分:明确的回退路径、跳过条件、故障开放/关闭机制
10分:全面的错误分类、恢复流程、用户沟通机制

证据:引用任何错误处理内容或说明其缺失情况

DIMENSION 8 — Monitoring & Observability (weight: low-medium)

维度8 — 监控与可观测性(权重:低-中)

Skip if skill type doesn't involve running infrastructure
1-3:  No monitoring guidance
4-6:  Mentions monitoring exists
7-9:  Specific metrics, queries, or dashboards provided
10:   Full observability setup: metrics, alerts, dashboards, interpretation

Evidence: Quote monitoring-related content

若Skill类型不涉及运行基础设施,可跳过
1-3分:无监控指导
4-6分:提及监控存在
7-9分:提供特定指标、查询或仪表盘
10分:完整可观测性设置:指标、告警、仪表盘、解读说明

证据:引用监控相关内容

DIMENSION 9 — Documentation Quality (weight: medium)

维度9 — 文档质量(权重:中)

1-3:  Minimal explanation, hard to understand intent
4-6:  Reasonable documentation, some gaps
7-9:  Clear phases, explains trade-offs, good inline comments
10:   Exemplary documentation, teaches concepts not just steps

Evidence: Note structure quality, comment density, explanation depth

1-3分:说明极少,难以理解意图
4-6分:文档质量尚可,存在部分空白
7-9分:阶段清晰,解释权衡,内联注释完善
10分:文档范例,不仅教授步骤还讲解概念

证据:记录结构质量、注释密度、解释深度

DIMENSION 10 — Freshness & Maintenance (weight: medium)

维度10 — 时效性与维护性(权重:中)

1-3:  Outdated (>2 years), references deprecated tools/versions
4-6:  Somewhat current, minor outdated references
7-9:  Recent, pinned versions, CVE awareness
10:   Actively maintained, latest versions, security bulletins referenced

Evidence: Note version numbers, dates, any outdated references

1-3分:过时(超过2年),引用已废弃工具/版本
4-6分:较为当前,存在少量过时引用
7-9分:近期更新,版本固定,具备CVE意识
10分:持续维护,使用最新版本,引用安全公告

证据:记录版本号、日期、任何过时引用

PHASE 4 — Comparison Table

阶段4 — 对比表格

Generate the structured comparison table.
生成结构化对比表格。

Format A — Single Skill Analysis (no alternative)

格式A — 单个Skill分析(无替代方案)

markdown
undefined
markdown
undefined

Skill Analysis: [skill name]

Skill分析: [skill name]

Source: [URL or file] Language: [language] Security: [Trust Hub: X | Socket: X | Audit: X]
DimensionScoreEvidence
Scope & GeneralityN/10"[quote or finding]"
Technical DepthN/10"[quote or finding]"
Decision IntelligenceN/10"[quote or finding]"
ORM CompatibilityN/10"[quote or finding]"
Security PracticesN/10"[quote or finding]"
Output QualityN/10"[quote or finding]"
Error HandlingN/10"[quote or finding]"
MonitoringN/10"[quote or finding]"
DocumentationN/10"[quote or finding]"
FreshnessN/10"[quote or finding]"
TOTALN/100
Verdict: [ADOPT / ADAPT / REPLACE / BUILD FROM SCRATCH]
undefined
来源: [URL或文件] 语言: [language] 安全: [Trust Hub: X | Socket: X | Audit: X]
维度评分证据
范围与通用性N/10"[引用或发现内容]"
技术深度N/10"[引用或发现内容]"
决策智能N/10"[引用或发现内容]"
ORM兼容性N/10"[引用或发现内容]"
安全实践N/10"[引用或发现内容]"
输出质量N/10"[引用或发现内容]"
错误处理N/10"[引用或发现内容]"
监控N/10"[引用或发现内容]"
文档N/10"[引用或发现内容]"
时效性N/10"[引用或发现内容]"
总分N/100
结论: [ADOPT / ADAPT / REPLACE / BUILD FROM SCRATCH]
undefined

Format B — Side-by-Side Comparison (two skills)

格式B — 两两对比(两个Skill)

markdown
undefined
markdown
undefined

Skill Comparison

Skill对比

Dimension[Skill A][Skill B]Winner
LanguageSpanishEnglishSkill B
ScopeSingle projectGeneral purposeSkill B
Pool mode selectionFixed: transactionAnalyzes & selectsSkill B
Pool size calculationHardcoded (25, 500)Formula-derivedSkill B
ORM compatibilityasyncpg onlyDrizzle/Prisma/TypeORM/SQLAlchemySkill B
CVE checkNoneCVE-2025-12819 includedSkill B
Capacity analysisNoneRAM/CPU/connection formulaSkill B
SecurityAudit: FAIL ❌passes skill-security ✅Skill B
Weekly installs7Skill A (existing users)
Config styleStatic copy-pasteDynamic, project-adaptiveSkill B
ScoreN/100N/100
undefined
维度[Skill A][Skill B]胜出者
语言SpanishEnglishSkill B
范围单个项目通用型Skill B
池模式选择固定:transaction分析并选择Skill B
池大小计算硬编码(25, 500)公式推导Skill B
ORM兼容性仅asyncpgDrizzle/Prisma/TypeORM/SQLAlchemySkill B
CVE检查包含CVE-2025-12819Skill B
容量分析RAM/CPU/连接公式Skill B
安全Audit: FAIL ❌通过skill-security ✅Skill B
周安装量7Skill A(已有用户)
配置风格静态复制粘贴动态适配项目Skill B
评分N/100N/100
undefined

Format C — Ecosystem Gap Analysis (multiple skills)

格式C — 生态系统差距分析(多个Skill)

markdown
undefined
markdown
undefined

Ecosystem Coverage Analysis

生态系统覆盖分析

Goal: [what you want to achieve]
CapabilityExisting SkillCoverageGap
Schema designschema-architect✅ Full
Index optimizationindex-advisor✅ Full
Connection poolingpgbouncer (skills.sh)⚠️ PartialNo mode selection, hardcoded values
Migration planning❌ NoneNeeds new skill
CDC pipeline❌ NoneNeeds new skill

---
目标: [你想要实现的内容]
能力现有Skill覆盖情况差距
Schema设计schema-architect✅ 完全覆盖
索引优化index-advisor✅ 完全覆盖
连接池pgbouncer (skills.sh)⚠️ 部分覆盖无模式选择,存在硬编码值
迁移规划❌ 无覆盖需要新Skill
CDC流水线❌ 无覆盖需要新Skill

---

PHASE 5 — Gap Analysis

阶段5 — 差距分析

If gaps found, produce
skill-gap-list.md
:
markdown
undefined
若发现差距,生成
skill-gap-list.md
文件:
markdown
undefined

Skill Gap Analysis

Skill差距分析

Critical Gaps (blocking — must fix)

关键差距(阻塞性——必须修复)

  1. [Gap name]
    • What's missing: [description]
    • Why it matters: [impact]
    • Suggested fix: [add section / rewrite / new skill]
  1. [差距名称]
    • 缺失内容: [描述]
    • 影响: [说明重要性]
    • 建议修复方案: [添加章节/重写/新Skill]

Important Gaps (should fix)

重要差距(应当修复)

...
...

Minor Gaps (nice to have)

次要差距(锦上添花)

...

---
...

---

PHASE 6 — Build or Adopt Recommendation

阶段6 — 采用或构建建议

Final recommendation with reasoning:
markdown
undefined
最终建议及理由:
markdown
undefined

Recommendation: [ADOPT / ADAPT / BUILD FROM SCRATCH]

建议: [ADOPT / ADAPT / BUILD FROM SCRATCH]

ADOPT — Use as-is

ADOPT — 直接使用

When: score >75/100, language matches, scope fits, security passes → Install instructions:
npx skills add [URL]
→ No changes needed
适用场景: 评分>75/100,语言匹配,范围符合,安全通过 → 安装指令:
npx skills add [URL]
→ 无需修改

ADAPT — Fork and modify

ADAPT — 分叉并修改

When: score 50-75/100, good foundation but specific gaps → Start with existing skill → Required changes: [specific list] → Estimated effort: [X hours]
适用场景: 评分50-75/100,基础良好但存在特定差距 → 基于现有Skill开始 → 需修改内容: [具体列表] → 预估工作量: [X小时]

BUILD FROM SCRATCH

BUILD FROM SCRATCH — 从零构建

When: score <50/100, wrong language, too narrow scope, security failures → Existing skill is a reference at best → Use gap analysis as requirements → Estimated effort: [X hours] → Key sections to include: [list]

---
适用场景: 评分<50/100,语言不符,范围过窄,安全失败 → 现有Skill仅可作为参考 → 将差距分析作为需求 → 预估工作量: [X小时] → 需包含的核心章节: [列表]

---

PHASE 7 — Output Files

阶段7 — 输出文件

All output files MUST be written to the
docs/skill-report/
directory to keep the user's workspace clean and standardized.
所有输出文件必须写入
docs/skill-report/
目录,以保持用户工作区整洁规范。

docs/skill-report/skill-analysis-report.md

docs/skill-report/skill-analysis-report.md

Full report combining Phases 3-6:
  • Skill metadata
  • 10-dimension scoring table with evidence (with dynamically scaling max points)
  • Comparison table (if comparing two skills)
  • Summary of strengths and weaknesses
整合阶段3-6的完整报告:
  • Skill元数据
  • 带证据的10维度评分表(动态调整满分)
  • 对比表格(若对比两个Skill)
  • 优缺点总结

docs/skill-report/skill-gap-list.md

docs/skill-report/skill-gap-list.md

(Only if gaps found)
  • Structured gap list by priority
  • Each gap with impact and fix suggestion
(仅当发现差距时生成)
  • 按优先级排序的结构化差距列表
  • 每个差距包含影响和修复建议

docs/skill-report/build-or-adopt.md

docs/skill-report/build-or-adopt.md

  • Clear recommendation (ADOPT / ADAPT / BUILD)
  • Justification
  • If ADAPT: specific changes needed
  • If BUILD: requirements derived from gap analysis

  • 明确建议(ADOPT / ADAPT / BUILD)
  • 理由说明
  • 若为ADAPT:具体修改需求
  • 若为BUILD:基于差距分析的需求列表

USAGE EXAMPLES

使用示例

Example 1 — Analyze a skills.sh skill

示例1 — 分析skills.sh上的Skill

User: "Analyze https://skills.sh/davidcastagnetoa/skills/pgbouncer"

→ Fetch page
→ Extract SKILL.md content + security audit results
→ Score 10 dimensions
→ Note: Spanish, single project, hardcoded values, Audit FAIL
→ Verdict: BUILD FROM SCRATCH
→ Gap list: mode selection, pool sizing formula, ORM matrix, CVE check
用户: "分析https://skills.sh/davidcastagnetoa/skills/pgbouncer"

→ 获取页面
→ 提取SKILL.md内容 + 安全审计结果
→ 10维度评分
→ 记录:西班牙语、单个项目、硬编码值、Audit FAIL
→ 结论:BUILD FROM SCRATCH
→ 差距列表:模式选择、池大小计算公式、ORM矩阵、CVE检查

Example 2 — Compare two skills

示例2 — 对比两个Skill

User: "Compare https://skills.sh/X/skills/Y with my skill [uploads SKILL.md]"

→ Fetch external skill
→ Read uploaded skill
→ Score both on all dimensions
→ Side-by-side table
→ Highlight winners per dimension
→ Overall recommendation
用户: "对比https://skills.sh/X/skills/Y和我的Skill [上传SKILL.md]"

→ 获取外部Skill
→ 读取上传的Skill
→ 对两者进行全维度评分
→ 生成两两对比表格
→ 突出各维度胜出者
→ 给出整体建议

Example 3 — Ecosystem gap analysis

示例3 — 生态系统差距分析

User: "I need PostgreSQL skills. What exists and what's missing?"

→ Search skills.sh for PostgreSQL skills
→ Fetch top 5 results
→ Map to capability matrix
→ Identify gaps
→ Prioritized build list
用户: "我需要PostgreSQL相关Skill。现有哪些,缺少什么?"

→ 在skills.sh上搜索PostgreSQL相关Skill
→ 获取前5个结果
→ 映射到能力矩阵
→ 识别差距
→ 生成优先级构建列表

Example 4 — Quick verdict

示例4 — 快速结论

User: "Is this skill good? [pastes SKILL.md]"

→ Read content
→ Rapid 10-dimension scan
→ Single verdict table + 2-sentence summary
→ One recommendation

用户: "这个Skill好用吗?[粘贴SKILL.md内容]"

→ 阅读内容
→ 快速扫描10维度
→ 生成简洁评分表 + 2句话总结
→ 给出单一建议

SCORING CALIBRATION

评分校准

Use this to ensure consistent scoring:
9-10: Best-in-class. Hard to improve.
7-8:  Solid. Minor improvements possible.
5-6:  Adequate. Clear gaps but usable.
3-4:  Below average. Significant missing pieces.
1-2:  Poor. Fundamental problems.

Never give 10/10 unless it truly cannot be improved.
Never give 1/10 unless it's actively harmful.
Always justify with evidence from the skill content.

使用以下标准确保评分一致性:
9-10分:同类最佳,难以改进。
7-8分:优秀,可进行小幅优化。
5-6分:合格,存在明确差距但可用。
3-4分:低于平均水平,存在重大缺失。
1-2分:较差,存在根本性问题。

除非确实无法改进,否则切勿给10分。
除非存在主动危害,否则切勿给1分。
始终以Skill内容中的证据为依据。

SKIP CONDITIONS

跳过条件

  • User just wants to install a skill without analysis → help install, skip analysis
  • Skill is internal/private and cannot be fetched → ask user to paste content
  • User says "just tell me if it's good" → Phase 3 only, quick table, skip full report
  • 用户仅需安装Skill而无需分析 → 协助安装,跳过分析
  • Skill为内部/私有且无法获取 → 请用户粘贴内容
  • 用户要求"直接告诉我好不好" → 仅执行阶段3,生成快速表格,跳过完整报告