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research-topic-extractor

当用户明确要求"从文件/图片/网页/描述中提取综述主题"、"生成主题+关键词+核心问题结构化输出",或要求使用旧名 get-review-theme skill 时使用。支持文件(PDF/Word/Markdown/Tex)、文件夹、图片、自然语言描述、网页 URL 等多种输入源,自动识别输入类型并提取内容,生成可直接用于 research-literature-review 及其他文献综述技能的结构化输出。

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

63%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.

The body lays out a clear, reasonably actionable extraction workflow with good failure handling, but is diluted by generic constraint boilerplate and squanders its one reference file by never linking to it. Fixing the orphaned reference and trimming the common-constraints block would lift both conciseness and progressive disclosure.

Suggestions

Reference the existing references/prompt_templates.md from the body (e.g. under 语义提取: 'prompt 模板见 [prompt_templates.md](references/prompt_templates.md)') so its templates and per-input-type guidance are actually discoverable.

Add a concrete example of the structured output (one short text or yaml block showing 主题/关键词/核心问题) so the required format is unambiguous without inference.

Trim or externalize the 公共硬约束 and bensz-collect-bugs boilerplate that is unrelated to topic extraction, keeping only the skill-specific constraints inline.

DimensionReasoningScore

Conciseness

The core flow sections (识别输入类型, 提取内容, 语义提取, 校验, 失败与恢复) are lean bullet lists, but a large share of the body is generic infrastructure boilerplate — the bensz-collect-bugs procedure and the 8-bullet 公共硬约束 block — that does not advance topic extraction and could be tightened or externalized, matching 'mostly efficient but includes some unnecessary explanation'.

3 / 5

Actionability

Guidance is concrete for an instruction-only skill: per-input-type handling ("图片:依赖 LLM 原生视觉能力", "文件夹:递归扫描并合并 .md/.txt/.pdf"), numeric output specs ("5-10 个英文标准术语", "2-5 个具体研究问题"), and per-failure recovery actions. Not 5 because the body never shows a concrete example of the text/yaml/json output the skill must produce, leaving the format specification to inference.

4 / 5

Workflow Clarity

A clear sequence runs 输入 → 识别输入类型 → 提取内容 → 语义提取 → 格式化 → 输出, with a 校验 checkpoint and a dedicated 失败与恢复 section covering five failure modes. Not 5 because validation is a static checklist with no explicit feedback loop (e.g. 'if 校验 fails, regenerate') tying it back into re-extraction.

4 / 5

Progressive Disclosure

The bundle contains references/prompt_templates.md with genuinely useful prompt templates and per-input-type guidance, but the body never mentions or links it — the reference is orphaned, so Claude would never load it and its content goes unused. This matches 'references present but not clearly signaled'; not 2 because the body itself is well-sectioned and short enough to stand alone.

3 / 5

Total

14

/

20

Passed

Description

92%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: it states concrete capabilities with comprehensive input coverage, gives explicit 'use when' triggers with quoted phrasings, and proactively manages the legacy skill name to avoid misrouting. Only minor keyword-synonym coverage keeps trigger term quality from the top score.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "自动识别输入类型并提取内容", "生成主题+关键词+核心问题结构化输出", output "可直接用于 research-literature-review" — and comprehensively enumerates supported inputs ("PDF/Word/Markdown/Tex、文件夹、图片、自然语言描述、网页 URL"), matching the comprehensive-coverage anchor rather than the minor-gaps anchor at 4.

5 / 5

Completeness

Both 'what' (extract structured review topics from files/images/web/descriptions) and 'when' ("当用户明确要求...时使用") are explicitly answered with concrete quoted trigger phrases, exactly matching the top anchor; not 4 because the 'when' clause is fully explicit rather than merely adequate.

5 / 5

Trigger Term Quality

Natural trigger phrases users would actually say are quoted directly ("从文件/图片/网页/描述中提取综述主题", "生成主题+关键词+核心问题结构化输出") plus the legacy alias "get-review-theme", but a few common variations (e.g. English phrasings like 'literature review topic') are missing, so it sits between anchors 4 and 5 but closer to 4.

4 / 5

Distinctiveness Conflict Risk

It carves a clear niche (structured topic extraction feeding research-literature-review rather than performing the review) and handles the legacy-name conflict explicitly by routing "get-review-theme" triggers to this skill, matching the clear-niche/minimal-conflict anchor; generic file-extraction overlap is neutralized by the '综述主题' qualifier.

5 / 5

Total

19

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository

huangwb8/ChineseResearchLaTeX

Path

skills/research-topic-extractor/SKILL.md

Reviewed

Table of Contents

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