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Analyze Product Behavior with Mixpanel
Discover event/property schemas, then analyze funnels, retention, cohorts, paths, or revenue metrics.
Skills
Discover real event and property names, query methods, and result types before building an analysis around the user’s question. Define denominators, time windows, timezone, and cohort rules. Combine funnel, retention, flow, or profile queries where useful and state the data scope. If updating business-context Markdown, get authorization and write only to a reviewable document; do not alter raw event data.
Permissions
Prerequisites
- Authorized Mixpanel project access, `mixpanel_headless`, and its Python dependencies; discover event names from that project.
Permissions
- Reads project event and user analytics that may be personal behavioral data; may write business-context files at the user’s request. Limit fields, purpose, and storage for results or exports.
Limitations
Query coverage and output depend on project mode, event instrumentation, and API limits. Correlation, cohort differences, and funnel drop-off alone do not prove causation.
Pinned upstream source
- Repository
- openai/plugins
- File path
- plugins/mixpanel-headless/skills/mixpanelyst/SKILL.md
- Pinned commit
0722921d5542fc593105c27bd52630babd8b8c2a- Source checked
- 2026-10-14 · Reviewed against the pinned upstream source
Repository metrics
These values describe the upstream repository, not popularity or likes for an individual skill or playbook.
- Stars
- Not collected
- Forks
- Not collected
- Observed at
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No metrics snapshot is available yet.
License: MIT
Compatible tools
Mixpanel Headless / Python
Main topic
Turn ecommerce campaign materials into a reviewable weekly brief