Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cnfeat/top-pm-skills --skill data-analysis-standardgit clone --depth 1 https://github.com/cnfeat/top-pm-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cnfeat/top-pm-skills/data-analysis-standard)<a href="https://agentmods.dev/skills/cnfeat/top-pm-skills/data-analysis-standard"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/data-analysis-standard/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cnfeat/top-pm-skills/data-analysis-standard"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/data-analysis-standard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00071 | $0.01181 |
| Opus 5 | $0.00036 | $0.00590 |
| Sonnet 5 | $0.00014 | $0.00236 |
| Haiku 4.5 | $0.00007 | $0.00118 |
Grade A, and why
data-analysis-standard scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Analysis Standard Skill
Turn raw numbers into product decisions. Structure every analysis with a clear question, methodology, finding, and recommended action.
Analysis Framework: The 4-Question Method
Every analysis starts here:
- What changed? (describe the metric and its movement)
- Why did it change? (root cause — segment, funnel step, cohort, channel)
- So what? (business or product impact)
- Now what? (recommended action with confidence level)
Never deliver data without answering all four. A chart with no narrative is not an analysis.
Metric Triage Template
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]
Funnel Analysis Structure
| 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]
Cohort Analysis Guidelines
Always define:
- Cohort definition: [What groups users — signup week, first action, plan type]
- Retention metric: [What counts as retained — login, core action, revenue]
- Retention window: [D1, D7, D30, W4, M3, etc.]
Output a cohort retention table and annotate:
- Baseline retention for each cohort
- Cohorts that over/underperform and why (feature launch? campaign? seasonal?)
- Trend direction across cohorts (improving / declining / stable)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 135 lines · 71 tokens per session scan A 835e14c313d2
data-analysis-standard is a skill published in the GitHub repository cnfeat/top-pm-skills (48 stars, last pushed 2mo ago), licensed MIT. It adds 71 tokens to every session and 1,181 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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