data-analysis

Analyze datasets to extract insights, identify patterns, and generate reports. Use when exploring data, creating visualizations, or performing statistical analysis. Handles CSV, JSON, SQL queries, and Python pandas operations.

3.36x

Quality

78%

Does it follow best practices?

Impact

64%

3.36x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

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npx tessl skill review --optimize ./.agent-skills/data-analysis/SKILL.md

Evaluation results

56%

44%

Retail Sales Data Preparation

Data cleaning workflow

Criteria

Without context

With context

Imports pandas and numpy

100%

Calls df.info()

Calls df.describe()

Calls df.head(10)

Checks missing values

100%

Checks dtypes

100%

Fills missing with mean

Drops rows missing required fields

Removes duplicates

100%

Converts date column

100%

Converts to category type

100%

IQR outlier removal

46%

100%

Works on a copy

Documents process

100%

51%

23%

E-Commerce Product Performance Analysis

Statistical analysis and visualization

Criteria

Without context

With context

Uses groupby with agg()

100%

Computes correlation

100%

Uses pivot_table

100%

Imports seaborn

100%

Histogram saved as histogram.png

Histogram uses bins=30

Boxplot saved as boxplot.png

Heatmap saved as heatmap.png

Heatmap uses annot=True and cmap='coolwarm'

100%

Time series saved as timeseries.png

Correct histogram/boxplot figsize

42%

Correct heatmap figsize

Correct time series figsize

100%

Works on copy

100%

86%

67%

Customer Segment Performance Review

Insights and report generation

Criteria

Without context

With context

Top 10 with nlargest

57%

Bottom 10 with nsmallest

57%

Monthly groupby for trend

100%

pct_change for growth

100%

Segment agg with revenue/orders

100%

avg_order_value computed

100%

Report has 4 sections

20%

100%

Dataset overview content

62%

Statistical summary table

100%

Recommendations section

100%

Conclusions supported by data

71%

100%

Works on copy

20%

Documents process

80%

100%

Repository: supercent-io/skills-template
Commit: c033769

Evaluated: 28 days ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Retail Sales Data Preparation E-Commerce Product Performance Analysis Customer Segment Performance Review

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