alexe-ev Plan Event Instrumentation
Purpose
Help teams define the event tracking plan for a product area — what user actions to instrument, what properties to capture, and what decisions the data will support.
Skill type
Conceptual skill
Use this skill when
- A feature is being built and analytics instrumentation needs to be defined
- Existing tracking is inconsistent or missing key events
- A metrics framework has been defined but instrumentation hasn't been planned
- Analytics debt has accumulated and a tracking audit is needed
Do not use this skill when
- Metrics framework hasn't been defined yet (use design-product-metrics first)
- The goal is dashboard design (use build-decision-dashboard)
Required inputs
- Feature or product area to instrument
- Key metrics or decisions the tracking should support
Optional inputs
- Existing tracking schema or event taxonomy
- Analytics tooling (Mixpanel, Amplitude, Segment, etc.)
- Engineering constraints on instrumentation
Upstream context
Works best when:
- Metrics framework is defined
- Feature requirements are written
Downstream handoff
Output can feed:
- build-decision-dashboard (instrumented events feed dashboard)
- analyze-funnel-retention-cohorts (events enable funnel and cohort analysis)
Instructions
- Map the user actions in the feature that are worth tracking.
- For each action, define: event name, trigger condition, and required properties.
- Follow a consistent naming convention (e.g., object_action format).
- Define which properties to capture per event (user ID, session, feature context, etc.).
- Identify funnel entry and exit events.
- Define identity and session tracking requirements.
- Review for coverage: are all key metrics measurable with the planned events?
Output
Provide:
- Event tracking plan (event name, trigger, properties)
- Naming convention and taxonomy
- Funnel events identified
- Identity and session tracking approach
- Coverage check: metrics vs. planned events
- Engineering implementation notes
- Events not covered and why
Risks / caveats
- Instrumentation planned after shipping creates analytics debt — plan before development
- Over-tracking creates noise and storage costs — focus on decision-relevant events
- Property naming inconsistency across events creates analysis friction