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sn-da-non-spreadsheet-analysis

Word / PDF / PPT 文档解析与数据分析引擎。覆盖三类文件格式的全量提取、表格数值化、图表理解与跨文档汇总分析。**遇到以下任一情况就主动使用本 skill**:①用户上传或指定了 .docx / .doc / .pdf / .pptx / .ppt 文件并要求分析、提取或统计其中内容;②用户出现触发词:Word分析 / PDF解析 / PPT提取 / 文档分析 / 报告解析 / 幻灯片分析 / 发票提取 / 合同分析 / 文档统计 / 错别字 / 语病 / 字号检查 / 简历分析 / 多文档对比;③任务涉及从文档中提取表格、数值、图表、格式(颜色/高亮/字号)、组织架构、时间线等结构化信息。仅不用于:Excel/CSV 数据分析(使用 sn-da-excel-workflow)、纯图片分析(使用 sn-da-image-caption)。

79

Quality

100%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

The body is a tight, executable workflow overview with clear sequencing, verification checkpoints, and well-signaled one-level-deep references to format sub-skills. It respects Claude's competence without over-explaining.

DimensionReasoningScore

Conciseness

Lean and well-organized with no padding or explanation of concepts Claude already knows; every code block and bullet earns its place.

3 / 3

Actionability

Provides fully executable Python (file-type detection, routing, verification prints, a complete caption_image helper with subprocess and error handling) plus concrete caption prompts, all copy-paste ready.

3 / 3

Workflow Clarity

Steps 0–3 are explicitly sequenced with a verification checkpoint in Step 3 (spot-check, intermediate values, unit confirmation) and error handling for the batch/directory case, satisfying the validation requirement for batch operations.

3 / 3

Progressive Disclosure

SKILL.md acts as a concise overview pointing to one-level-deep sub-skills via a routing table and an 'Available sub-skills' section; references are clearly signaled and no nested/deep references exist (no bundle files present in the skill directory).

3 / 3

Total

12

/

12

Passed

Description

100%

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

The description is specific, trigger-rich, and explicitly states both capabilities and use-conditions while disambiguating from sibling skills. It uses directive rather than first/second-person voice, satisfying the third-person requirement.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — '全量提取、表格数值化、图表理解与跨文档汇总分析' — naming the domain and specific operations rather than vague language.

3 / 3

Completeness

Clearly answers both 'what' (解析与数据分析引擎 with listed capabilities) and 'when' via the explicit '遇到以下任一情况就主动使用本 skill' clause with three numbered trigger scenarios.

3 / 3

Trigger Term Quality

Provides broad coverage of natural user terms ('Word分析 / PDF解析 / PPT提取 / 发票提取 / 合同分析 / 简历分析 / 多文档对比') alongside file extensions, matching what a user would actually say.

3 / 3

Distinctiveness Conflict Risk

Explicit exclusions ('仅不用于:Excel/CSV 数据分析… 纯图片分析') with named sibling skills carve out a clear niche unlikely to trigger the wrong skill.

3 / 3

Total

12

/

12

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

15

/

16

Passed

Repository
OpenSenseNova/SenseNova-Skills
Reviewed

Table of Contents

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