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图片理解与数据提取 skill。当图片文件(.png/.jpg/.jpeg/.gif/.webp/.bmp)是主要输入且用户需要理解、提取数据或分析图片内容时使用。提供预配置的 caption 脚本(scripts/caption.py),通过 vision 模型将图片转为文本描述,无需额外配置 API Key。覆盖:(1) 通过 scripts/caption.py 对图表/表格/截图/流程图进行 caption,(2) 将 caption 文本解析为结构化 DataFrame,(3) 基于提取数据重新生成可视化图表,(4) 导出为 Excel/CSV。**遇到以下任一情况就主动使用本 skill,不要自行猜测图片内容**:①用户出现触发词:图片分析 / 图表提取 / 表格识别 / OCR / 图片描述 / 截图分析 / 图表数据 / 提取图片中的数据 / 图片转表格 / 识别图片 / image caption / extract data from image / chart analysis / table OCR;②用户上传或指定了图片文件(.png / .jpg / .jpeg / .gif / .webp / .bmp)并要求理解、提取数据或分析内容;③任务需要从图表截图、表格截图、UI 截图、流程图中提取结构化信息;④用户要求将图片中的数据转为 Excel/CSV 或重新生成可视化图表。仅不用于:图片编辑(裁剪、滤镜、缩放)、图片生成、不含数据的风景/人物照片描述。

73

Quality

91%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

82%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 is highly actionable with executable code throughout and a clear core workflow. Its main weaknesses are minor: some inline code blocks could move to reference files, and verification checkpoints live in Common Pitfalls rather than inline in the workflow.

Suggestions

Promote the 'verify extracted data' guidance from Common Pitfalls into an explicit numbered checkpoint in the Overview workflow (e.g., step 3: validate row counts/sums before exporting), strengthening the batch-operation feedback loop.

Move the long parse_markdown_table function and the openpyxl Excel-styling boilerplate into a references/ file (e.g., references/parsing.py, references/export.py) and link to them from SKILL.md to improve progressive disclosure and conciseness.

Tighten the Excel export snippet to the essential to_excel call plus a one-line note on styling, trimming inline token cost.

DimensionReasoningScore

Conciseness

Mostly lean — it does not explain concepts Claude already knows and leads with executable code — but the full parse_markdown_table function and openpyxl styling boilerplate are long inline blocks that could be trimmed, keeping it just below the lean/efficient anchor.

4 / 5

Actionability

Fully executable, copy-paste-ready code and CLI commands cover the common cases (single image, custom prompt, JSON, batch, Python invocation, parsing, visualization, Excel export), matching the fully-executable anchor.

5 / 5

Workflow Clarity

The Overview gives a clear caption→parse→analyze/visualize/export sequence and Common Pitfalls supplies verification (check sums/percentages/row counts, two-pass for truncation), but validation is stated in a separate pitfalls section rather than as an inline checkpoint, leaving a minor gap below the explicit-feedback-loop anchor.

4 / 5

Progressive Disclosure

Well-organized sections with the scripts/caption.py bundle correctly referenced and no nested references, though the parsing/visualization/export code is inlined rather than split into reference files, sitting just below the clear-overview-with-one-level-references anchor.

4 / 5

Total

17

/

20

Passed

Description

100%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.

The description is concrete, trigger-rich, and explicitly separates what/when with a clear negative boundary. It is somewhat long, but the content is specific rather than padded fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete actions with comprehensive coverage — caption via scripts/caption.py, parse caption to structured DataFrame, regenerate visualization charts, and export to Excel/CSV — matching the anchor for several specific concrete actions.

5 / 5

Completeness

Explicitly answers both 'what' (caption→parse→visualize→export) and 'when' via four numbered trigger conditions with concrete trigger phrases, plus an explicit negative-boundary clause.

5 / 5

Trigger Term Quality

Comprehensive natural-term coverage including synonyms and file extensions: 图片分析/图表提取/表格识别/OCR/图片描述/截图分析/image caption/extract data from image plus .png/.jpg/.jpeg/.gif/.webp/.bmp, matching the comprehensive-synonyms-and-extensions anchor.

5 / 5

Distinctiveness Conflict Risk

Clear niche (image caption/data extraction) with distinct triggers and an explicit 'not for' boundary (image editing, generation, non-data photos), giving minimal conflict risk.

5 / 5

Total

20

/

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

relative_links

Relative link issues: 2 suspicious

Warning

Total

15

/

16

Passed

Repository
OpenSenseNova/SenseNova-Skills
Reviewed

Table of Contents

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