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Skill Quality Scorer
作者
Chris1Wang3
· GitHub ↗
· v1.1.7
· MIT-0
48
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版本数
在 OpenClaw 中安装
/install skill-quality-scorer
功能描述
Deterministic TRACE+ quality scorer for Agent Skills (SKILL.md): six dimensions T-R-F-S-I-E, 30 sub-items, merges TRACE, good-skill authoring reverse-rubric...
使用说明 (SKILL.md)
\r \r
Skill Quality Scorer · 技能质量评分器\r
\r
EN TRACE+ (T-R-F-S-I-E) × 30 sub-items · static script first · formula score · JSON + Markdown. \r 中文 TRACE+ 六维 30 子项 · 先 static_audit · 公式算分 · JSON + Markdown。\r \r When / 何时用： 迭代没方向 · 对标同类 · 发布前自检 · 批量评
skills/\r Not / 不用： 从零写 Skill · 替代 skill-eval 行为实验（E 维默认static_proxy）\r \r
Score portfolio-doctor with TRACE+ — where vs skill-reviewer?\r
给 portfolio-doctor 做 TRACE+ 全维评分。\r
```\r
\r
## 评测模式\r
\r
| 模式 | 输出 |\r
|------|------|\r
| 单个 | JSON + Markdown（[audit-playbook](references/audit-playbook.md)） |\r
| A vs B | 两份 JSON + 分差表 + 推荐 |\r
| 批量 | 汇总表 + 各 skill 简评 |\r
\r
对比/批量：**同一 rubric v2**，不得换公式或跳过子项。\r
\r
## 工作流\r
\r
```text\r
1) 定位 skill 目录（对比/批量则逐个重复 2–6）\r
2) python scripts/static_audit.py "\x3Cskill-dir>" → auto_scores（不可改分）\r
3) Read scoring-engine-deterministic.md → 30 子项 evidence\r
4) Read 目标 SKILL.md + 链接的 references/scripts\r
5) composite = round((T+R+F+S+I+E)×100/60, 1) → 评级 + Verdict\r
6) 按 audit-playbook 输出（含 F 维触发测试各 ≥3 条）\r
```\r
\r
评级 / Verdict / 30 子项定义 / JSON schema → [scoring-engine-deterministic.md](references/scoring-engine-deterministic.md)\r
\r
## 硬约束\r
\r
1. 先脚本后 rubric；`auto_scores` 只补 evidence 不改分\r
2. 30 子项逐项 evidence；禁止旧公式 `(T+R+A+C+E)×2`\r
3. E 维默认 `static_proxy`；有 skill-eval 时切换 `behavioral_eval`\r
4. **Rigid**：子项、公式、Verdict 不可改 · **Flexible**：evidence 表述、Top 修复排序\r
\r
## 参考文件\r
\r
| 文件 | 内容 |\r
|------|------|\r
| [references/scoring-engine-deterministic.md](references/scoring-engine-deterministic.md) | 30 子项 rubric · 公式 · JSON schema |\r
| [references/audit-playbook.md](references/audit-playbook.md) | 报告模板 · 对比/批量 · 触发测试 |\r
| [examples/sample-score-v2.json](examples/sample-score-v2.json) | JSON 样例 |\r
| [scripts/static_audit.py](scripts/static_audit.py) | 静态审计（唯一运行时脚本） |\r
安全使用建议
Install only if you want an agent to inspect local skill directories for quality scoring. Run it on directories you intentionally choose, avoid pointing it at unrelated private workspaces, and treat its scoring as an advisory review aid rather than a substitute for behavioral testing or human security review.
能力标签
能力评估
Purpose & Capability
The stated purpose is to score Agent Skills using a TRACE+ rubric, and the artifacts match that purpose: SKILL.md defines the workflow, references provide the 30-item rubric and report templates, and the Python script performs local static checks used as inputs.
Instruction Scope
The skill instructs the agent to read a target skill directory, linked references, and scripts, and to run `python scripts/static_audit.py <skill-dir>`. That file access is broad if the user points it at a large or private skill tree, but it is disclosed and directly tied to the scoring task.
Install Mechanism
No package installation, network bootstrap, allowlist edits, service restarts, or external dependency setup are present. The only executable component is a bundled Python script using standard-library parsing and local file reads.
Credentials
Reviewing skills can expose local skill contents, including any credentials accidentally stored in those files. This is proportionate for a skill auditor, but users should choose the target directory deliberately.
Persistence & Privilege
The artifacts show no background worker, persistence mechanism, privilege escalation, filesystem mutation, network calls, or credential/session-store use.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install skill-quality-scorer - 安装完成后，直接呼叫该 Skill 的名称或使用
/skill-quality-scorer触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.1.7
- No user-facing or functional changes in this version.
- SKILL.md remains unchanged; no updates to features, workflow, or documentation.
- Version bump only; existing behavior and scoring logic are retained.
v1.1.6
- Removed redundant documentation files: README.md, README-zh.md, and skill-card.md.
- Simplified and clarified SKILL.md, focusing on workflow, evaluation modes, and constraints.
- Added concise bilingual (EN/中文) summary and clearer usage guidance.
- Centralized details (e.g., rubric definition, formula, schema) into reference files.
- No logic or code changes; documentation update only.
v1.1.5
- Added detailed documentation on the 6-dimension, 30-subitem TRACE+ quality scoring system, including formulas, workflows, and rigid evaluation rules.
- Clarified supported evaluation modes: single, comparison (A vs B), and batch, with required output formats.
- Specified static_audit.py as the mandatory first step; manual scoring must follow automated results and standardized rubric.
- Defined strict pass/fail/conditional verdicts and grade thresholds based on composite scores and critical flags.
- Enumerated fixed constraints and provided references for all rule sources, scoring schemas, and template formats.
元数据
常见问题
Skill Quality Scorer 是什么？
Deterministic TRACE+ quality scorer for Agent Skills (SKILL.md): six dimensions T-R-F-S-I-E, 30 sub-items, merges TRACE, good-skill authoring reverse-rubric... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 48 次。
如何安装 Skill Quality Scorer？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install skill-quality-scorer」即可一键安装，无需额外配置。
Skill Quality Scorer 是免费的吗？
是的，Skill Quality Scorer 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Skill Quality Scorer 支持哪些平台？
Skill Quality Scorer 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Skill Quality Scorer？
由 Chris1Wang3（@chris1wang3）开发并维护，当前版本 v1.1.7。
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