Creates instrumentation specs for analytics event tracking, defining events, triggers, properties, user attributes, PII handling, and QA checklists for features and experiments.
From pm-skillsnpx claudepluginhub product-on-purpose/pm-skillsThis skill uses the workspace's default tool permissions.
references/EXAMPLE.mdreferences/TEMPLATE.mdGuides agentic engineering workflows: eval-first loops, 15-min task decomposition, model routing (Haiku/Sonnet/Opus), AI code reviews, and cost tracking.
Designs and optimizes AI agent action spaces, tool definitions, observation formats, error recovery, and context for higher task completion rates.
Enables AI agents to execute x402 payments with per-task budgets, spending controls, and non-custodial wallets via MCP tools. Use when agents pay for APIs, services, or other agents.
An instrumentation spec defines what analytics events to track, when to fire them, and what properties to include. It serves as a contract between product and engineering, ensuring consistent data collection that enables accurate measurement. Good instrumentation specs prevent the "we can't answer that question because we didn't track it" problem.
When asked to create an instrumentation spec, follow these steps:
Define Analytics Goals Start with the questions you need to answer. What will you measure? What decisions will this data inform? This prevents over-instrumentation while ensuring nothing important is missed.
Identify Events to Track
List each user action or system event that should be tracked. Follow consistent naming conventions (typically noun_verb or verb_noun in snake_case). Each event should represent a distinct, meaningful action.
Specify Event Triggers For each event, describe exactly when it fires. Be precise: "When user clicks Submit button" vs. "When form is submitted successfully." These are different events with different meanings.
Define Event Properties List the properties (attributes) attached to each event. Include property name, data type, description, and example values. Properties provide context that makes events useful.
Document User Properties Identify persistent user-level attributes that should be associated with all events (e.g., subscription tier, account creation date). These enable segmentation in analysis.
Address PII and Privacy Flag any properties that contain personally identifiable information. Document how PII should be handled — hashing, encryption, or exclusion.
Create Testing Checklist Define how QA should verify that tracking is implemented correctly. Include steps to validate events fire at the right times with correct properties.
Use the template in references/TEMPLATE.md to structure the output.
Before finalizing, verify:
See references/EXAMPLE.md for a completed example.