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multi-sheet-reading-and-analysis

用于读取多工作表Excel文件,动态评估数据量以启用Parquet大文件优化,并执行正则清洗、分类汇总、线性拟合及生成带格式的图表与结果文件。

59

Quality

68%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./skills/sn-da-excel-workflow/capability/excel-reading/multi-sheet-reading/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%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 skill delivers a concrete, mostly executable 4-step Excel analysis pipeline with lean prose, but lacks validation/verification checkpoints (capping workflow clarity) and is monolithic with no progressive disclosure.

Suggestions

Add validation checkpoints between steps — e.g., verify the file loaded and sheets were counted, confirm cleaned columns are non-empty, and assert the output file exists after save — to lift workflow clarity above the batch-operation cap of 3.

Replace the placeholder demo DataFrame in Step 3 with real extraction from df (groupby/aggregation on actual columns) so the analysis step is fully executable rather than illustrative.

Move the verbose Step 4 styling block into a referenced helper file (e.g., scripts/report_styling.py) and signal it from SKILL.md to introduce progressive disclosure and reduce inline length.

DimensionReasoningScore

Conciseness

The body is mostly lean — each step is a one-line description followed by code with functional comments, and it avoids explaining concepts Claude already knows — but the Step 4 styling block and Step 3 placeholder demo data add some length that could be trimmed.

4 / 5

Actionability

Provides mostly executable Python across all four steps, but column-name placeholders ('your_excel_file.xlsx', '目标清洗列', 'X轴列') and the hardcoded demo DataFrame in Step 3 keep it just short of copy-paste-ready.

4 / 5

Workflow Clarity

Four steps are clearly sequenced (count/convert → clean → analyze → report), but validation checkpoints are absent throughout; because multi-sheet processing and file generation are batch operations, the rubric caps workflow clarity at 3.

3 / 5

Progressive Disclosure

Content is organized into four numbered steps giving reasonable structure, but it is a monolithic single-file skill (~148 lines) with all code inlined and no external references or navigation, fitting the some-structure-but-could-be-better-organized anchor.

3 / 5

Total

14

/

20

Passed

Description

71%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 specific and comprehensive about what the skill does, but omits any explicit 'when to use' trigger guidance, which caps completeness. Trigger terms are good but lack synonyms and file extensions.

Suggestions

Add an explicit 'Use when...' clause stating when Claude should invoke this skill (e.g., 'Use when the user provides a multi-sheet Excel file and asks for cleaning, aggregation, fitting, or formatted reporting').

Include natural synonyms and the .xlsx file extension in the description to broaden trigger-term coverage.

Keep the concrete action list but pair it with concrete trigger phrases users would actually say.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — '读取多工作表Excel文件', '动态评估数据量以启用Parquet大文件优化', '正则清洗', '分类汇总', '线性拟合', '生成带格式的图表与结果文件' — covering the full pipeline comprehensively, matching the comprehensive-coverage anchor.

5 / 5

Completeness

The 'what' is clearly and thoroughly stated, but there is no 'Use when...' clause or equivalent trigger guidance; per the rubric cap, a missing explicit 'when' caps completeness at 3.

3 / 5

Trigger Term Quality

Good natural keyword coverage ('Excel文件', '多工作表', '图表', '结果文件'), but misses common synonyms and file extensions (no '.xlsx', 'spreadsheet/表格', '数据透视表'), so it sits below the comprehensive-coverage anchor.

4 / 5

Distinctiveness Conflict Risk

The specific combination of multi-sheet reading, Parquet large-file optimization, regex cleaning, and linear fitting is mostly distinct, with only minor overlap risk against generic Excel/data-analysis skills.

4 / 5

Total

16

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
OpenSenseNova/SenseNova-Skills
Reviewed

Table of Contents

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