Analytics Event Spec (Clean)
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Prompt Content
# Analytics Event Specification Generator
## Role
You are a technical analytics specialist responsible for creating standardized event tracking specifications.
## Task
Generate a comprehensive analytics event specification table for {{feature}} in Markdown format.
## Output Format
Create a table with the following columns:
- Event Name
- Trigger Conditions
- Required Properties
- Sample JSON Payload
## Requirements
- Event names should follow snake_case convention
- All timestamps must be in ISO 8601 format
- Properties should be camelCase
- JSON payload must be properly formatted and indented
- Include only essential properties that provide meaningful insights
- Each event should have a clear, specific trigger condition
## Example Structure
| Event Name | Trigger Conditions | Required Properties | Sample Payload |
|------------|-------------------|---------------------|----------------|
| feature_action | When user performs X | - userId<br>- timestamp<br>- actionType | ```json {...}``` |
## Additional Guidelines
- Include user identification properties where applicable
- Add session/context information when relevant
- Ensure all property names are self-descriptive
- Document any dependencies or prerequisites
- Specify data types for each property
## Constraints
- Maximum 5 events per feature
- Maximum 10 properties per event
- All property values must be properly typed
- No sensitive/PII data in sample payloadsHow to use Analytics Event Spec (Clean)
Use this template as a starting point for analytics, tracking, technical. Read the full prompt first, then adapt the details so the model has enough context to produce a useful answer.
- Copy the prompt: Start with the full template so the structure stays intact.
- Replace placeholders: Swap bracketed notes or generic examples with your real goal, audience, constraints, and source material.
- Add success criteria: Tell the model what a good answer should include, avoid, or prioritize.
- Iterate once: If the first answer misses the mark, ask for a revision with one concrete change.
Prompt engineering tips
- Use the tags as guardrails: Keep the output focused on analytics, tracking, technical.
- Define the role: Tell the model what expert perspective it should use before it answers.
- Set the format: Specify whether you want bullets, a table, code, a checklist, or a polished draft.
Best use cases
Analytics Event Spec (Clean) is most useful for people working on analytics and tracking. It works best when you have a clear input, a specific output format, and enough background detail for the model to avoid generic advice.
- Turn a rough idea into a structured first draft.
- Create a repeatable workflow for analytics, tracking, technical.
- Compare several options before choosing the final direction.
Customization checklist
Before running the prompt, add the details that make your situation different from a generic example. The strongest results usually include constraints, examples, audience notes, and a clear definition of done.
- Add your audience, product, role, industry, or project context.
- Include examples of what good and bad output looks like.
- Ask for one final review pass for clarity, accuracy, and missing assumptions.
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