tracking-spec-writer

To generate a tracking plan from a product PRD, the system translates product requirements and core user journeys into complete tracking schemes covering event definitions, field dictionaries, trigger timing, metric definitions, and QA checklists. It outputs interactive HTML documents with embedded design doc panels and executable acceptance SQL queries.

Event design and field definition for data collection involve standardizing event naming conventions, defining trigger timing, checking cross-event field conflicts, and validating enum completeness for string-type business fields. This ensures data tracking schemes are complete, consistent, and executable across cross-functional teams.

Executable acceptance SQL queries for metric specification are created automatically alongside the tracking documentation. The system outputs interactive HTML documents containing these queries, enabling QA and analytics teams to validate data tracking schemes and verify paired events like start or complete.

Yes, you can use oral descriptions to build data tracking schemes. The system translates flowcharts, core user journeys, and oral descriptions into standardized tracking plans, enforcing consistent event naming conventions and ensuring paired events are fully defined for development and QA teams.

Manual tracking plan design leads to inconsistent event naming, incomplete field definitions, and outputs that are hard for development, QA, and analytics teams to execute. Automating the creation of standardized tracking and metric design documents eliminates these friction points and ensures enum completeness.

The best way to validate paired events in a tracking scheme is to use automated standardization checks. The system ensures paired events like action start and action fail are fully defined, checks for cross-event field conflicts, and generates interactive QA checklists for immediate verification.