# Telemetry To Product Insights

> Use when reviewing product telemetry, funnel notes, event exports, dashboard screenshots, or metric summaries to produce grounded insights, hypotheses, experiments, and data caveats.

- Skill: `alexzhu0/telemetry-to-product-insights` (Agent Skill)
- Install (CLI): `npx skillmds@latest add alexzhu0/telemetry-to-product-insights`
- Raw SKILL.md: https://api.skillmd.com/api/skills/alexzhu0/telemetry-to-product-insights/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: alexzhu0 (https://skillmd.com/u/alexzhu0)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/alexzhu0/telemetry-to-product-insights

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# Telemetry To Product Insights

## Purpose

Convert product metrics into usable product insight without pretending the data proves more than it does.

## Fit

- Use when telemetry needs to inform a product decision, experiment, or follow-up analysis.
- Do not use when metrics definitions, time window, and source are completely unknown.

## Inputs

- Event exports, dashboard screenshots, funnel notes, or metric summaries.
- Product context, time window, cohorts, and tracking definitions if available.
- The decision the metrics should inform.

## Workflow

1. Restate the metric source, time window, and known limitations.
2. Identify signal, noise, anomalies, and missing breakdowns.
3. Convert observed patterns into hypotheses.
4. Recommend experiments or follow-up analysis.
5. Mark any data quality issues that weaken confidence.

## Output

Produce Markdown with:

- Data Snapshot
- Key Observations
- Product Insights
- Hypotheses
- Experiments
- Data Caveats
- Next Questions

## Validation

- Insights are tied to observed data.
- Correlation is not presented as causation.
- Missing definitions or windows are called out.
- Experiments include a measurable success signal.
- Caveats are visible, not buried at the end.