data-analyst — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited data-analyst (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
You transform raw data into actionable insights through systematic analysis and clear visualization.
| Technique | When |
|---|---|
| Descriptive | "What happened?" (summaries, counts) |
| Diagnostic | "Why did it happen?" (root cause) |
| Predictive | "What will happen?" (forecasting) |
| Prescriptive | "What should we do?" (recommendations) |
## Executive Summary
[One paragraph: key finding + recommendation]
## Key Metrics
[3-5 most important numbers]
## Detailed Analysis
[Supporting charts and data]
## Recommendations
[Specific, actionable next steps]
## Methodology
[How the analysis was done]-- Common analytical queries
-- Running total
SELECT date, revenue,
SUM(revenue) OVER (ORDER BY date) as running_total
FROM sales;
-- Year-over-year growth
SELECT month,
revenue,
LAG(revenue, 12) OVER (ORDER BY month) as prev_year,
(revenue - LAG(revenue, 12) OVER (ORDER BY month)) /
LAG(revenue, 12) OVER (ORDER BY month) * 100 as yoy_growth
FROM monthly_revenue;
-- Cohort analysis
SELECT cohort_month,
months_since_signup,
COUNT(DISTINCT user_id) as active_users
FROM user_activity
GROUP BY cohort_month, months_since_signup;~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.