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law-to-markdown

律师助理与法律助手在处理繁杂法条时,当需要将 PDF/Word/TXT 格式的法律规范文件转为结构化 Markdown 时适用。自动完成 OCR 解析、法律层级识别与三阶段保真校验,一键生成排版完美的法条 Markdown 文档及审核报告,让法律文本数字化工作事半功倍。

Quality

90%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-engineered skill body: executable commands, a documented and verified parameter surface, and a validation-first workflow with explicit feedback loops. The remaining gaps are minor — duplicated artifact-level/output rules and no mention of the requirements.txt dependency file or helper scripts in the bundle.

DimensionReasoningScore

Conciseness

The body is rule-dense with no explanation of concepts Claude already knows, and every section carries operational information. Not a 5 because `artifact-level` defaults and the non-law output rules are each stated twice (in 三阶段参数/输出规则 and again under 可通过命令参数切换/非法律文档), which could be consolidated.

4 / 5

Actionability

Fully executable, copy-paste-ready commands ("python3 law-to-markdown/scripts/law_to_markdown.py \"input.txt\"") covering the common cases — txt, docx, pdf, and the consent-gated fallback variants — and every documented flag (--law-decision, --skip-stage3-check, --stage3-strict, --artifact-level, --out) verifies against the script's actual argparse surface.

5 / 5

Workflow Clarity

The three-stage pipeline is clearly sequenced with explicit validation checkpoints (Stage3-A text fidelity, Stage3-B structural checks), a defined failure feedback loop ("任一失败触发自动重走,最多 2 次;仍失败默认报错退出"), a non-law rejection path, and a safe no-op path when structure is unrecognized. This matches the top anchor including error recovery.

5 / 5

Progressive Disclosure

Well-organized sections with all overview-level content appropriately inline and detailed logic correctly delegated to the scripts bundle. Not a 5: the bundle's other files (cn_law_normalizer.py, stage3_checker.py, requirements.txt) get no navigation or mention, and dependency installation for the fallback engines is never surfaced despite requirements.txt existing.

4 / 5

Total

18

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: explicit 'use when' trigger with concrete formats, a specific capability list, and a distinct legal-domain niche. The only weakness is mild promotional filler ("排版完美", "事半功倍") and slightly incomplete synonym/extension coverage in trigger terms.

DimensionReasoningScore

Specificity

The description names the input formats ("PDF/Word/TXT 格式的法律规范文件") and several concrete actions — "OCR 解析、法律层级识别与三阶段保真校验" plus generation of a Markdown document and review report. Not a 5 because it stops short of naming the structural elements it produces (e.g., 条/章/节 hierarchy levels), and the closing marketing phrase adds no capability.

4 / 5

Completeness

Both what and when are explicitly answered: the when clause "当需要将 PDF/Word/TXT 格式的法律规范文件转为结构化 Markdown 时适用" is an explicit 'Use when' equivalent with concrete triggers, and the what covers OCR parsing, hierarchy recognition, three-stage verification, and output generation. Matches the top anchor; the trailing filler sentence does not obscure either answer.

5 / 5

Trigger Term Quality

Good natural keyword coverage: "法条", "法律规范文件", "PDF/Word/TXT", "结构化 Markdown", "OCR", "审核报告". A few natural terms are missing — no file extensions (.docx, .pdf), and no common synonyms such as "法规" or "条文" that a user might say.

4 / 5

Distinctiveness Conflict Risk

It carves out a clear niche — converting legal normative documents into structured Markdown with fidelity checking — which is distinct from generic PDF/OCR/document-conversion skills. Triggers are domain-specific (法条, 法律规范) with minimal conflict risk against general document tools.

5 / 5

Total

18

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

anbeime/skill

Path

skills/legal-assistant-skills-main/law-to-markdown/SKILL.md

Reviewed

Table of Contents

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