SkillCompass MCP — 使用场景, 安装 & 实时演示

为什么要用

核心特性

Multi-dimensional skill scoring (clarity, activation, correctness, cost)
'Weakest link' identification across a bundle
Suggests concrete SKILL.md edits
Before/after eval harness
JavaScript tooling — runs locally

实时演示

实际使用效果

skillcompass-skill.replay ▶ 就绪

0/0

安装

选择你的客户端

~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "skillcompass-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/Evol-ai/SkillCompass",
        "~/.claude/skills/SkillCompass"
      ],
      "_inferred": true
    }
  }
}

打开 Claude Desktop → Settings → Developer → Edit Config。保存后重启应用。

~/.cursor/mcp.json · .cursor/mcp.json

{
  "mcpServers": {
    "skillcompass-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/Evol-ai/SkillCompass",
        "~/.claude/skills/SkillCompass"
      ],
      "_inferred": true
    }
  }
}

Cursor 使用与 Claude Desktop 相同的 mcpServers 格式。项目级配置优先于全局。

VS Code → Cline → MCP Servers → Edit

{
  "mcpServers": {
    "skillcompass-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/Evol-ai/SkillCompass",
        "~/.claude/skills/SkillCompass"
      ],
      "_inferred": true
    }
  }
}

点击 Cline 侧栏中的 MCP Servers 图标，然后选 "Edit Configuration"。

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "skillcompass-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/Evol-ai/SkillCompass",
        "~/.claude/skills/SkillCompass"
      ],
      "_inferred": true
    }
  }
}

格式与 Claude Desktop 相同。重启 Windsurf 生效。

~/.continue/config.json

{
  "mcpServers": [
    {
      "name": "skillcompass-skill",
      "command": "git",
      "args": [
        "clone",
        "https://github.com/Evol-ai/SkillCompass",
        "~/.claude/skills/SkillCompass"
      ]
    }
  ]
}

Continue 使用服务器对象数组，而非映射。

~/.config/zed/settings.json

{
  "context_servers": {
    "skillcompass-skill": {
      "command": {
        "path": "git",
        "args": [
          "clone",
          "https://github.com/Evol-ai/SkillCompass",
          "~/.claude/skills/SkillCompass"
        ]
      }
    }
  }
}

加入 context_servers。Zed 保存后热重载。

claude mcp add skillcompass-skill -- git clone https://github.com/Evol-ai/SkillCompass ~/.claude/skills/SkillCompass

一行命令搞定。用 claude mcp list 验证，claude mcp remove 卸载。

使用场景

实战用法： SkillCompass

Find the skill pulling your agent's performance down

👤 Skill authors with 5+ skills installed ⏱ ~45 min advanced

何时使用： You feel the agent has gotten worse, not better, as you added skills.

前置条件

Node 20+ — nvm install 20
Skill cloned and installed — git clone https://github.com/Evol-ai/SkillCompass ~/.claude/skills/SkillCompass; npm i

步骤

Run the evaluator

Score all skills in ~/.claude/skills/ — show me the weakest link.✓ 已复制

→ Ranked skill list with per-dimension scores
Diagnose the loser

For the weakest skill, what specifically is wrong?✓ 已复制

→ Concrete critique (vague description, conflicting with other skill, etc.)
Propose a fix

Suggest a minimal edit to SKILL.md to fix it.✓ 已复制

→ Small, reviewable diff
Re-evaluate

Re-run the eval and show before/after.✓ 已复制

→ Metrics improved, with evidence

结果： A measurably better skill bundle, with a reproducible eval process.

注意事项

Gaming the eval metric instead of helping real tasks — Include task-level downstream metrics (actual agent outcomes), not just text-level

搭配使用： skill-optimizer-skill · filesystem

Review a new skill before you publish it

👤 Skill authors shipping their first bundle ⏱ ~20 min intermediate

何时使用： Before pushing to GitHub and telling the world about your skill.

步骤

Score the draft

Evaluate my draft skill at ./my-skill/.✓ 已复制

→ Dimension scores
Fix obvious issues

Apply the low-hanging suggestions✓ 已复制

→ Edits in SKILL.md

结果： A publication-ready skill rather than a rough draft.

注意事项

Chasing a perfect score — Ship when scores plateau — diminishing returns

组合

与其他 MCP 搭配，撬动十倍杠杆

skillcompass-skill + skill-optimizer-skill

Two complementary tools: SkillCompass ranks, skill-optimizer drills into SKILL.md patterns

Use SkillCompass to pick the worst skill; use skill-optimizer to deeply analyze its SKILL.md.✓ 已复制

skillcompass-skill + filesystem

Operate across the full ~/.claude/skills/ directory

Evaluate every skill in ~/.claude/skills/ and give me a CSV.✓ 已复制

工具

此 MCP 暴露的能力

工具	输入参数	何时调用	成本
skill-scoring	skill path(s)	Periodic audits	eval compute
weakest-link-id	bundle scores	After scoring	0
fix-suggestion	weak skill + critique	Before editing	0
before-after-eval	pre/post SKILL.md	After applying fixes	eval compute

成本与限制

运行它的成本

API 配额: none beyond your LLM provider (evals use LLM calls)
每次调用 Token 数: evals can be heavy — budget 20–100k tokens for a full bundle scan
费用: free, MIT
提示: Run on one skill at a time during iteration; bundle runs only for audits

安全

权限、密钥、影响范围

凭据存储： none at skill level

数据出站： none beyond your LLM provider

故障排查

常见错误与修复

Node errors on install

Ensure Node 20+; npm i inside the skill directory.

验证： node -v

Evals are inconsistent run-to-run

Fix the task seed and use a non-stochastic sample; record provider+model.

替代方案

SkillCompass 对比其他方案

替代方案	何时用它替代	权衡
skill-optimizer-skill	You want a single skill analyzed deeply rather than a bundle ranked	Depth over breadth
manual review	You have 1–2 skills total	Doesn't scale

SkillCompass

为什么要用

核心特性

实时演示

实际使用效果

安装

选择你的客户端

使用场景

实战用法： SkillCompass

Find the skill pulling your agent's performance down

前置条件

步骤

注意事项

Review a new skill before you publish it

步骤

注意事项

组合

与其他 MCP 搭配，撬动十倍杠杆

工具

此 MCP 暴露的能力

成本与限制

运行它的成本

安全

权限、密钥、影响范围

故障排查

常见错误与修复

替代方案

SkillCompass 对比其他方案

更多

资源