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churn-analysis-helper

Churn Analysis Helper - Auto-activating skill for Data Analytics. Triggers on: churn analysis helper, churn analysis helper Part of the Data Analytics skill category.

36

1.03x

Quality

3%

Does it follow best practices?

Impact

97%

1.03x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./planned-skills/generated/12-data-analytics/churn-analysis-helper/SKILL.md
SKILL.md
Quality
Evals
Security

Evaluation results

98%

7%

Customer Churn Rate Analysis

SQL churn rate computation

Criteria
Without context
With context

SQL used for data retrieval

83%

100%

Monthly churn computed

100%

100%

Churn rate formula present

100%

100%

CSV output produced

100%

100%

Production-ready code structure

90%

100%

Error handling or defensive code

75%

75%

Methodology documented

100%

100%

Step-by-step explanation

75%

100%

Industry-standard churn definition

100%

100%

Output validated or summarised

80%

100%

Without context: $0.4305 · 1m 40s · 23 turns · 65 in / 7,498 out tokens

With context: $0.7019 · 2m 25s · 36 turns · 67 in / 9,460 out tokens

100%

3%

Churn Dashboard Report

Churn visualization and BI reporting

Criteria
Without context
With context

Trend chart produced

100%

100%

Segment comparison chart

100%

100%

Charts use labels and titles

100%

100%

Report file produced

100%

100%

Business recommendation present

100%

100%

BI framing of findings

70%

100%

Highest-risk segment identified

100%

100%

Charts referenced in report

100%

100%

Trend direction stated

100%

100%

Script is self-contained

100%

100%

Without context: $0.2691 · 1m 30s · 17 turns · 17 in / 4,693 out tokens

With context: $0.5986 · 2m 16s · 31 turns · 288 in / 8,282 out tokens

95%

1%

Cohort Retention and Churn Predictor Analysis

Statistical cohort churn analysis

Criteria
Without context
With context

Cohort grouping by month

100%

100%

Retention rates at multiple horizons

100%

100%

Statistical comparison method named

100%

100%

Q1 vs non-Q1 comparison made

100%

100%

Significance or effect stated

100%

100%

Analysis documented step by step

100%

100%

Results validated or cross-checked

80%

70%

Industry-standard retention definition

100%

100%

CSV output correct structure

60%

80%

Clear conclusion in summary

100%

100%

Without context: $0.4066 · 1m 37s · 19 turns · 19 in / 6,379 out tokens

With context: $0.6241 · 2m 27s · 27 turns · 27 in / 9,640 out tokens

Repository
jeremylongshore/claude-code-plugins-plus-skills
Evaluated
Agent
Claude Code
Model
Claude Sonnet 4.6

Table of Contents

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