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statistical-distribution-and-outlier-analysis

执行数值型数据的分布分析与异常值检测,支持通过正则表达式从文本中提取误差项并生成高分辨率的箱线图与直方图报告。

63

Quality

73%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./skills/sn-da-excel-workflow/capability/excel-data-visualization/histogram-visualization/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

80%

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

The content is a lean, fully-executable six-step Python pipeline with strong actionability and conciseness, but it lacks explicit validation checkpoints in the workflow and is a monolithic single file with no overview or navigation structure.

Suggestions

Add an explicit validation/checkpoint between steps (e.g. after Step 3, print and confirm outlier counts are sane before generating charts) to lift workflow clarity toward 3.

Add a brief overview line at the top summarizing the pipeline and, if the skill grows, move the longer plotting code into a references/ script to give progressive disclosure a clear overview-plus-reference structure.

DimensionReasoningScore

Conciseness

The body is code-forward with only brief functional comments (e.g. '# 设置中文字体', '# 处理可能的合并单元格空值') and no conceptual explanations of things Claude already knows, matching the 'lean and efficient; every token earns its place' anchor.

3 / 3

Actionability

Each of the six steps provides complete, executable Python (e.g. pd.read_excel, boxplot, IQR computation, re.findall with a concrete pattern), copy-paste ready, matching the 'fully executable code; specific examples' anchor.

3 / 3

Workflow Clarity

Steps are clearly numbered and sequenced (Step 1–6) with implicit guards (e.g. 'if extracted_errors:' / else branch), but there are no explicit validation or verification checkpoints confirming outputs before proceeding, fitting 'sequence present but checkpoints missing or implicit' rather than the explicit-validation level 3.

2 / 3

Progressive Disclosure

Content is well-sectioned into six steps with no nested references, but everything lives inline in a single ~147-line SKILL.md with no overview header or navigation pointers, matching 'content that should be separate is inline' / 'could be better organized' rather than the clear-overview-with-references level 3.

2 / 3

Total

10

/

12

Passed

Description

67%

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 distinctive, naming concrete actions and a clear niche, but it omits any explicit 'Use when...' trigger guidance and relies on technical jargon rather than natural user phrasing.

Suggestions

Add an explicit 'Use when...' trigger clause (e.g. 'Use when analyzing numerical data distributions, detecting outliers, or extracting error terms from text') to lift completeness to 3.

Include more natural user-facing keywords alongside the technical ones (e.g. '数据分析', '找异常值', '画箱线图') so trigger-term quality covers common variations.

DimensionReasoningScore

Specificity

Lists several concrete actions — '分布分析与异常值检测', '通过正则表达式从文本中提取误差项', '生成高分辨率的箱线图与直方图报告' — matching the 'lists multiple specific concrete actions' anchor, and not the level below which only names a domain plus some actions.

3 / 3

Completeness

It clearly answers 'what does this do', but there is no 'Use when...' clause or equivalent trigger guidance; per the judging guidelines a missing explicit trigger caps completeness at 2, and it is not a 1 because the 'what' is strong.

2 / 3

Trigger Term Quality

Keywords like '分布分析', '异常值检测', '正则表达式', '箱线图', '直方图' are relevant but lean technical; common user phrasings or variations (e.g. '数据分析', '找异常值') are missing, so it sits at 'some relevant keywords but missing common variations' rather than full natural-term coverage.

2 / 3

Distinctiveness Conflict Risk

The combination of regex error-term extraction with boxplot/histogram reporting on numerical data is a clear niche unlikely to trigger for unrelated skills, matching the 'clear niche with distinct triggers' anchor.

3 / 3

Total

10

/

12

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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