measure-experiment-design
Designs an A/B test or experiment with clear hypothesis, variants, success metrics, sample size, and duration. Use when planning experiments to validate product changes or test hypotheses.
What this skill does
<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 --> # Experiment Design An experiment design document defines all parameters needed to run a rigorous A/B test or controlled experiment. It ensures the team aligns on what you're testing, how you'll measure success, and how long to run the test before drawing conclusions. Good experiment design prevents common pitfalls: underpowered tests, unclear success criteria, and decisions based on noise rather than signal. ## When to Use - Before launching an A/B test to validate a product change - When testing a hypothesis that requires quantitative validation - After solution design to validate assumptions before full rollout - When stakeholders want data-driven evidence for a decision - To establish a culture of experimentation and learning ## Instructions When asked to design an experiment, follow these steps: 1. **Articulate the Hypothesis** Write a clear, testable hypothesis in the format: "We believe [change] for [users] will [outcome] as measured by [metric]." One hypothesis per experiment . if you're testing multiple things, run multiple experiments. 2. **Define the Variants** Describe the control (current experience) and treatment (new experience) in sufficient detail. Include screenshots, mockups, or precise descriptions so anyone can understand what users will see. 3. **Choose Primary and Secondary Metrics** Select one primary metric that will determine success or failure. Add 2-3 secondary metrics to understand the broader impact. Include guardrail metrics to catch unintended negative effects. 4. **Calculate Sample Size** Determine how many users you need per variant to detect your minimum detectable effect (MDE) with statistical significance. Specify your significance level (typically 0.05) and power (typically 0.80). 5. **Estimate Duration** Based on sample size and available traffic, calculate how long the experiment needs to run. Account for weekly patterns . avoid ending mid-week if behavior varies by day. 6. **Define Targeting and Allocation** Specify which users are eligible for the experiment and how traffic is split between variants. Document any exclusions (e.g., employees, specific segments). 7. **Set Success Criteria** Define upfront what constitutes a win, a loss, or an inconclusive result. This prevents post-hoc rationalization and moving goalposts. 8. **Document Risks and Mitigations** Identify what could go wrong and how you'll detect/address it. Include monitoring plans and rollback criteria. ## Output Format Use the template in `references/TEMPLATE.md` to structure the output. ## Quality Checklist Before finalizing, verify: - [ ] Hypothesis is falsifiable and specific - [ ] Only one primary metric is defined - [ ] Sample size calculation is documented with assumptions - [ ] Duration accounts for traffic patterns and statistical requirements - [ ] Success criteria are defined before the experiment starts - [ ] Guardrail metrics protect against unintended harm ## Examples See `references/EXAMPLE.md` for a completed example.
Related in Design
contribute
IncludedLocal-only OSS contribution command center. Auto-refreshes the user's in-flight PR and issue state on invoke so conversations start with full context — no need to brief Claude on what's in flight. Helps the user find issues to contribute to on GitHub, builds per-repo dossiers of what each upstream expects (CLA, DCO, branch convention, AI policy, draft-first, review bots, issue templates), runs deterministic gates before any external action so AI-assisted contributions don't reach maintainers as slop. State is markdown-only: candidate files at ~/.contribute-system/candidates/, repo dossiers at ~/.contribute-system/research/, append-only event log at ~/.contribute-system/log.jsonl. No database, no cloud calls. Use when the user asks about their PRs / issues / contributions, wants to find new work to take on, claim an issue, build/refresh a repo's dossier, or draft a Design Issue or PR. Trigger with "/contribute", "what's my PR status", "find a contribution", "claim issue X", "draft a Design Issue for Y", "refresh dossier for Z".
architectural-analysis
IncludedUser-triggered deep architectural analysis of a codebase or scoped subtree across eight modes — information architecture, data flow, integration points, UI surfaces, interaction patterns, data model, control flow, and failure modes. This skill should be used when the user asks to "diagram this codebase," "map the architecture," "show the data flow," "give me an ERD," "trace control flow," "find the integration points," "verify the layout pattern," "audit the UX architecture," or any similar request whose primary deliverable is mermaid diagrams plus cited reports under docs/architecture/. Dispatches haiku/sonnet sub-agents in parallel for per-mode exploration, then verifies every citation mechanically before any node lands in a diagram. Not for one-off prose explanations of code (use code-explanation) or for high-level system design from scratch (use system-design).
mcp
IncludedModel Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
react-native-skia
IncludedDesign, build, debug, and optimise high-polish animated graphics in React Native or Expo using @shopify/react-native-skia, Reanimated, and Gesture Handler. Use when the user wants canvas-driven UI, shaders, paths, rich text, image filters, sprite fields, Skottie, video frames, snapshots, web CanvasKit setup, or performance tuning for custom motion-heavy elements such as loaders, hero art, cards, charts, progress indicators, particle systems, or gesture-driven surfaces. Also use when the user asks for fluid, glow, glass, blob, parallax, 60fps/120fps, or GPU-friendly animated effects in React Native, even if they do not explicitly say "Skia". Do not use for ordinary form/layout work with standard views.
plaid
IncludedProduct Led AI Development — guides founders from idea to launched product. Six capabilities: Idea (discover a product idea), Validate (pressure-test the idea against fatal flaws, problem reality, competition, and 2-week MVP feasibility), Plan (vision intake + document generation), Design (translate image references into a design.md spec), Launch (go-to-market strategy), and Build (roadmap execution). Use when someone says "PLAID", "plaid idea", "help me find an idea", "product idea", "idea from my business", "idea from my expertise", "plaid validate", "validate my idea", "pressure-test", "is this idea good", "find fatal flaws", "validate the problem", "plan a product", "define my vision", "generate a PRD", "product strategy", "plaid design", "design from image", "translate image to design", "create design.md", "extract design tokens", "plaid launch", "go-to-market", "launch plan", "GTM strategy", "launch playbook", "plaid build", "build the app", "start building", or "execute the roadmap".
nextjs-framer-motion-animations
IncludedAdds production-safe Motion for React or Framer Motion animations to Next.js apps, including reveal, hover and tap micro-interactions, whileInView, stagger, AnimatePresence, layout and layoutId transitions, reorder, scroll-linked UI, and lightweight route-content transitions. Use when the user asks to add, refactor, or debug Motion or Framer Motion in App Router or Pages Router codebases, especially around server/client boundaries, reduced motion, LazyMotion, bundle size, hydration, or route transitions. Avoid for GSAP-style timelines, WebGL or 3D scenes, heavy scroll storytelling, or CSS-only effects unless Motion is explicitly requested.