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    Idea to PRD Generator

    by Arnstein Larsen

    1

    Turn a rough product idea into a buildable spec — with scope, assumptions, open questions, and success criteria your team can argue with.

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    See it in action

    You say

    I want to add a 'Save for Later' button to our e-commerce product pages. We use React and the goal is to reduce cart abandonment. Help me write a PRD for this.

    Your agent does

    PRD: Save for Later Feature Problem: Users add items to cart as a bookmark, leading to inflated abandonment. Scope: Heart icon on PDP, 'Saved' tab in account. Success: 10% increase in checkout conversion. Assumption: Users prefer a list over a browser bookmark.

    What you get

    Define feature scope and non-goals to prevent scope creepIdentify technical assumptions and validation plans before buildingGenerate structured one-pagers for stakeholder approvalUncover edge cases and functional requirements for engineering teams

    About this skill

    The gap between an idea and a buildable spec is where products quietly fail — teams start building from different mental models, discover the ambiguity mid-sprint, and either ship the wrong thing or blow the timeline resolving it. This skill converts a rough product idea into a PRD that gives engineers what they need to estimate, designers what they need to explore, and stakeholders what they need to approve: the problem being solved and for whom, the scope boundary (in / out of scope), the assumptions that need to hold for this to work, the open questions that must be answered before build, the success criteria that define done, and the constraints — technical, legal, timeline — the solution must work within. Describe your idea, the user problem, and any constraints; get back a structured PRD your team can push back on, not a blank page.

    Changelog

    1. v1.1LatestJun 26, 2026

      Rewrote the skill body with real, expert PM content. Every section now carries concrete PRD method (idea interrogation, problem statement tied to evidence, users & use cases with JTBD, functional requirements written as testable behaviour with edge cases, explicit non-goals & scope boundaries, success metrics that actually measure, assumptions & a cheap validation plan, open questions with named owners, rollout & release considerations, stakeholder-review readiness). Replaced the generic placeholder sections.

    2. v1.0Jun 11, 2026

      Initial release

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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