Build features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation.
SkillScore86Maintained
Automatic
◆Product Management pack
Last verified 8/29/2026
What it changes
Passed 19 of 22 test cases with the skill, and 18 of 22 without it.
Without skill82%
With skill86%
Checks it passed that the model alone missed
The response specifies consulting an analytics tracking plan document that defines event names and property schemas.
1 fixed18 passed either way3 still failing0 broke
Pass-rate lift
+5 pp
Tokens
+13%
Agent turns
0%
Response time
-2%
Model gemini-3.6-flashMeasured 8/29/2026v119 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
A test case the skill fixed. Same model, same prompt, with and without the skill.
Prompt
We are building a personalized discount banner in our app based on user churn probability. We have defined our goals and metrics, but we need deep code examples and detailed architectural templates for this data-driven feature rollout. Which reference document should we consult?
What was checked, without and with the skill
Checked
Without skill
With skill
The response specifies consulting an analytics tracking plan document that defines event names and property schemas.
Missed
Passed
case-07 · gemini-3.6-flash · 8/29/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md43 linessingle file
Data-Driven Feature Development
Build features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation.
[Extended thinking: This workflow orchestrates a comprehensive data-driven development process from initial data analysis and hypothesis formulation through feature implementation with integrated analytics, A/B testing infrastructure, and post-launch analysis. Each phase leverages specialized agents to ensure features are built based on data insights, properly instrumented for measurement, and validated through controlled experiments. The workflow emphasizes modern product analytics practices, statistical rigor in testing, and continuous learning from user behavior.]
Use this skill when
Working on data-driven feature development tasks or workflows
Needing guidance, best practices, or checklists for data-driven feature development
Do not use this skill when
The task is unrelated to data-driven feature development
You need a different domain or tool outside this scope
Instructions
Clarify goals, constraints, and required inputs.
Apply relevant best practices and validate outcomes.
Provide actionable steps and verification.
If detailed examples are required, open resources/implementation-playbook.md.