define-hypothesis
Defines a testable hypothesis with clear success metrics and a validation approach. Use when…
Creates a comprehensive Product Requirements Document that aligns stakeholders on what to build, why, and how success will be measured. Use when specifying features, epics, or product initiatives for engineering handoff.
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Creates a comprehensive Product Requirements Document that aligns stakeholders on what to build, why, and how success will be measured. Use when specifying features, epics, or product initiatives for engineering handoff.
name: deliver-prd description: Creates a comprehensive Product Requirements Document that aligns stakeholders on what to build, why, and how success will be measured. Use when specifying features, epics, or product initiatives for engineering handoff. license: Apache-2.0 metadata: phase: deliver version: "3.0.0" updated: 2026-08-21 category: specification frameworks: [triple-diamond, lean-startup, design-thinking] author: product-on-purpose
<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
A Product Requirements Document is the primary specification artifact that communicates what to build and why. It bridges the gap between problem understanding and engineering implementation by providing clear requirements, success criteria, and scope boundaries. A good PRD enables engineering to build the right thing while maintaining flexibility on implementation details.
When asked to create a PRD, follow these steps:
1. **Summarize the Problem** Start with a brief recap of the problem being solved. Link to the problem statement if available. Ensure readers understand *why* this work matters before diving into *what* to build.
2. **Define Goals and Success Metrics** Articulate what success looks like. Include specific, measurable metrics with baselines and targets. These metrics should connect directly to the problem being solved.
3. **Outline the Solution** Describe the proposed solution at a high level. Focus on user-facing functionality and key capabilities. Include enough detail for stakeholders to evaluate the approach without over-specifying implementation.
4. **Detail Functional Requirements** Break down what the system must do. Use user stories or requirement statements. Each requirement should be testable - someone should be able to verify if it's met.
5. **Link AI Behavior to Evidence** *(only when the feature's output comes from a model)* Skip this step entirely for deterministic features. When a model produces the output, the behavior varies run to run, so "it works" is a claim that needs evidence attached. Name the behaviors that are requirements of this release and, for each one, how it will be shown to hold and at what threshold. Refusal and abstention get their own rows: a model has no dependable default for either, so what the feature does when it should *not* answer is a requirement, not an implementation detail. Score each component of a multi-step feature separately, because an end-to-end pass rate hides which step failed. State how the case set was sized as a method, never as a borrowed number.
6. **Define Scope Boundaries** Explicitly state what's in scope, out of scope, and deferred to future iterations. Clear scope prevents scope creep and sets realistic expectations.
7. **Address Technical Considerations** Note any technical constraints, architectural decisions, or integration requirements. Don't design the system, but surface considerations engineering needs to know.
8. **Write the Agent Execution Contract** *(only when an executor will implement this without the authoring context)* Skip this step entirely when the implementers were in the room. A coding agent, an outside contractor, or a team picking this up cold cannot infer what you already know, so declare it: which sources are authoritative and which wins when two disagree, what must not be touched and why, how each FR-n is verified and by whom, and the conditions where the executor must stop and escalate rather than decide. Name an owner for every escalation; an escalation with no addressee becomes a guess. A requirement with no verification is not ready to hand off, because nothing distinguishes "done" from "the executor believes it is done".
9. **Identify Dependencies and Risks** List external dependencies, assumptions, and risks that could impact delivery. Include mitigation strategies where applicable.
10. **Propose Timeline and Milestones** Outline key phases and checkpoints. This helps stakeholders understand the delivery plan without committing to specific dates prematurely.
Active only when `.claude/pm-skills.local.md` exists. With no file, ignore this section entirely and behave exactly as described above.
`memory_auto_append: true` is set, in which case append and echo what was written.
produced the proposal. If it changed in between, merge your entry into the current state and re-propose rather than overwriting; add only your own entry and leave every other field and section byte-identical. Nothing enforces
68 plug-and-play, best-practice product management skills for AI agents: 30 Triple Diamond phase + 11 foundation + 12 utility + 15 tool (Foundation Sprint + Design Sprint). Plus 6 sub-agents, workflows, 200+ output samples, guides, and CI-enforced contracts. Apache 2.0.
Repo: product-on-purpose/pm-skills
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