Status: Shipped Milestone: v2.5.0 Issue: #108

Status: Backlog Milestone: v2.12.0 (candidate) Issue: TBD Agent: Claude Opus 4.7

Acceptance criteria define the observable behavior that must be true for a story or feature to be considered done. This skill turns feature context into concise, testable Given/When/Then scenarios that engineers and QA can verify without guessing intent.

An Architecture Decision Record documents a significant technical decision along with its context and consequences. ADRs capture the "why" behind architectural choices so future team members understand the reasoning — especially important when they question why something was done a particular way.

version: "1.0.0" updated: <YYYY-MM-DD> license: Apache-2.0 metadata: category: <one of: research, problem-framing, ideation, specification, validation, reflection, coordination> frameworks: [triple-diamond, lean-startup, design-thinking] author: product-on-purpose ---

A dashboard requirements document specifies what questions a dashboard should answer, what metrics it displays, and how data should be visualized. Clear requirements help data teams build dashboards that actually inform decisions rather than just displaying numbers.

Passing member: this directory exists, has a SKILL.md, and references the family contract path docs/reference/skill-families/demo-family-contract.md so the contract-reference branch passes.

Estimate market opportunity (TAM, SAM, SOM) using multiple sizing frameworks (top-down, bottom-up, comparable company, analogous market). Triangulates across frameworks, highlights where they converge and diverge as signal, and produces a calibrated range with source-graded confidence labels. Refuses unbounded fabrications; always offers a labeled lower-confidence path when data is thin. Used for investment cases, go/no-go decisions, and stakeholder pitches.

An edge cases document systematically catalogs the unusual, boundary, and error scenarios for a feature. While happy-path flows are typically well-specified, edge cases often get discovered in production — causing bugs, poor user experience, and support burden. Documenting edge cases upfront ensur

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: un

An experiment results document captures what happened when you tested a hypothesis, including statistical outcomes, segment analysis, learnings, and clear recommendations. Good results documentation turns individual experiments into organizational knowledge that improves future decision-making.

Placeholder skill directory for the WS-T9 dual-shell parity smoke. Carries no count-bearing phrases so only counts.md drives the fixture verdict.

Runs a fast pre-build risk review on a product idea, feature request, or scope change, naming the single assumption most likely to make it fail and returning a clear verdict (build small, validate first, pivot first, or don't build yet) with a no-code validation step. Use before committing build effort, when triaging whether to honor a feature request, or when deciding whether to expand scope, ahead of writing a PRD. For a launched product's pivot-or-persevere decision, use iterate-pivot-decision instead.

Produce a comprehensive, evidence-grounded prioritized action plan from any PM input (notes, transcripts, drafts, executive asks, Slack threads, or a raw situation). Outputs one saveable document with an executive summary, input mirror, situation classification (Cynefin), the binding constraint (Theory of Constraints), prioritized questions and open decisions, a ranked action plan with the critical effort plus follow-ons, risks and pre-mortem, copy/paste prompts for downstream pm-skills, and an evidence map. Builds a source ledger and cites exact input quotes; refuses High-confidence plans for Complex or Chaotic situations. Use when you want the critical next effort and how to execute it.

A hypothesis is a testable prediction about how a change will affect user behavior or business outcomes. It transforms assumptions into explicit statements that can be validated or invalidated through experimentation. Well-formed hypotheses prevent teams from building features based on untested beli

Initialize projects with agentic coding structure. Use when setting up a new project, adding AI agent support to existing project, or when user says "init", "initialize", "setup project", or "scaffold". Creates AGENTS folder, documentation templates, and _NOTES scratch space.

Initialize new JPKB projects with standardized documentation and folder structure. JPKB-specific version with category folders and fixed base path. Use when creating a new project in the jpkb repository, when the user says "init project", "new project", or when the target is the JPKB projects folder.

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 t

An interview synthesis transforms raw user research data into structured insights that drive product decisions. Rather than simply listing what participants said, a good synthesis identifies patterns across conversations, connects observations to underlying user needs, and translates findings into a