data-analysis-standard-e500ba — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited data-analysis-standard-e500ba (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.
Turn raw numbers into product decisions. Structure every analysis with a clear question, methodology, finding, and recommended action.
Every analysis starts here:
Never deliver data without answering all four. A chart with no narrative is not an analysis.
Use when a metric has moved unexpectedly:
METRIC: [Name]
MOVEMENT: [X% change over Y period]
BASELINE: [What was normal]
SEGMENTATION CHECK:
- By platform (iOS / Android / Web)?
- By user cohort (new / returning / power users)?
- By acquisition channel?
- By geography?
- By plan/tier?
ROOT CAUSE HYPOTHESIS:
1. [Most likely explanation] — Evidence: [data point]
2. [Alternative explanation] — Evidence: [data point]
3. [Ruling out] — Eliminated because: [reason]
CONCLUSION: [Single sentence answer to "why did this change?"]
CONFIDENCE: [High / Medium / Low] — based on [data available]| Stage | Metric | Current | Benchmark/Target | Drop-off % | Notes |
|---|---|---|---|---|---|
| [Top of funnel] | [Users] | [N] | [N] | — | |
| [Step 2] | [Users] | [N] | [N] | [X%] | |
| [Step 3] | [Users] | [N] | [N] | [X%] | |
| [Conversion] | [Users] | [N] | [N] | [X%] |
Biggest drop-off: [Step X → Step Y] — Hypothesis: [reason] Recommended investigation: [specific query or test]
Always define:
Output a cohort retention table and annotate:
Question being answered: [Specific question in plain English] Time period: [Date range] Data source: [Where data comes from]
Finding:
[1–2 sentence plain-English summary of what the data shows]
Key chart / table: [Include or describe]
Root cause: [Best explanation with evidence]
Confidence level: [High / Medium / Low] — [reason]
Recommended action:
What this analysis does NOT tell us: [Important caveat — what data is missing or what can't be concluded]
Work from what is given. If any of these is missing, still produce the complete output: fill each gap with a reasonable assumption marked (assumed, confirm) and list those assumptions at the end. Ask a question first only when the core subject itself is missing (there is nothing to write about).
This skill ships with support files — use them when they are available:
Score any output of this skill before handing it over; 32+ is ship-quality.
| Dimension | 0 | 5 | 10 |
|---|---|---|---|
| Four-question completeness | Describes what changed and stops | Covers what/why but "so what / now what" are thin | All four answered with proportionate depth; the "now what" is decision-ready |
| Evidence behind the root cause | Root cause asserted from intuition | One supporting data point, alternatives unexamined | Root cause tested against at least one rival explanation, with the discriminating evidence shown |
| Uncertainty honesty | Reads as certain; no confidence statement | Confidence stated but not justified | Confidence level justified, and "what the data cannot tell us" names the real blind spots, not token ones |
| Actionability | Findings with no action | Action named but ownerless or dateless | Recommended action has an owner, a timeline, and a stated expected effect worth checking later |
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.