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    Idea to PRD: An Honest Draft With Every Assumption Flagged

    1

    A short clarifying interview turns a one-liner into a structured PRD with per-section confidence scores. It never invents market data or sources.

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    Idea to PRD: An Honest Draft With Every Assumption Flagged

    Idea to PRD: An Honest Draft With Every Assumption Flagged

    Example session with this skill installed

    Turn my idea into a PRD: a retro tool where engineers can raise issues anonymously and the action items actually get done.

    • Read your context and instructions
    • Compiled the idea to prd

    Idea to PRD first runs a short clarifying interview (users, problem, competitors, business model, scope, constraints, success criteria). From the answers alone, with no research and nothing invented, it drafts:

    Draft PRD — forge-pulse-fast-feedback-team-heartbeat (v1)

    Problem (confidence 55%)

    Engineering teams run retrospectives but

    most action items die before the next sprint. The founder believes the root causes are (1) low psychological safety, so real issues go unspoken, and (2) no durable follow-through on the actions that do get raised.

    • Pain is felt most by individual contributors who don't feel safe raising problems.
    • Existing retro tools focus on the meeting, not on what happens after.

    ⚠️ ASSUMPTION: root-cause claims come from the founder's intuition, not validated user research.

    User Personas (confidence 50%)

    • IC engineer (primary): wants to raise real concerns without fear of attribution.
    • Team lead / facilitator: runs the retro and is accountable for follow-through.

    ⚠️ ASSUMPTION: persona pain points are inferred from the interview, not from interviews with real target users.

    Scope & Non-Goals (confidence 60%)

    In scope (MVP): anonymous feedback capture, simple upvoting, action items with owners.

    Non-goals: multiple retro formats, cross-team analytics, third-party integrations.

    ⚠️ ASSUMPTION: credible anonymity can be delivered in the MVP — not yet validated technically.

    Success Metrics (confidence 40%)

    • Action completion rate rises from an assumed baseline of ~40-50% to 70%+ within 3 months of adoption.
    • Participation: a majority of team members submit at least one note per retro.

    ⚠️ VAGUE_METRIC: baseline completion rate is assumed, not measured.
    ⚠️ UNKNOWN: no instrumentation plan for measuring completion.

    User Stories (confidence 65%)

    1. As an IC, I can submit a retro note anonymously so I can be honest.
    2. As a team, we can upvote notes so the most important themes rise.
    3. As a facilitator, I can turn a theme into an action item with an owner and due date.

    Technical Considerations (confidence 45%)

    • Real-time collaboration during the retro implies WebSockets.

    Anonymity is the hard part: the data model must not store authorship in a way a facilitator or admin could reverse.

    • Duplicate-vote prevention without identity is an open problem.

    ⚠️ ASSUMPTION: WebSockets are required — not yet validated against actual usage patterns.
    ⚠️ UNKNOWN: anonymous duplicate-vote prevention approach is undecided.

    Risks & Open Questions (confidence 50%)

    • The product may be

    solving a culture problem with tooling — tracking actions more visibly may not make teams complete them.

    • Free, established retro tools may be "good enough," making willingness-to-pay unclear.
    • Open question: who is the buyer, and is this a standalone product or a feature?

    ⚠️ RISK: tooling may not fix an organizational/culture problem.
    ⚠️ UNKNOWN: willingness to pay and the buyer are undetermined.

    Explicit assumptions

    • The core problem is low psychological safety plus poor follow-through (founder's hypothesis, unvalidated).
    • Teams will trust an anonymity guarantee enough to speak freely.
    • A standalone tool is worth adopting over existing free retro tools.

    Contradictions flagged

    • Notes are meant to be permanently anonymous, yet action items have named owners — an owner may be inferable from the note that spawned the action.

    Next: it points you to the lowest-confidence sections (Success Metrics at 40%, Technical Considerations at 45%) and the flagged assumptions as the things to validate first, and offers to red-team the draft.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Most AI-written PRDs read confidently and quietly invent things: market sizes, competitors, statistics, sources. Idea to PRD drafts only from what you actually told it, and flags everything else.

    How it works

    1. Give it an idea. A one-liner, a rough note, or a paragraph.
    2. Clarifying interview. Up to three rounds of 4–8 questions covering target users, the core problem and how painful it is, competitors, business model, scope and timeline, technical constraints, success criteria, and what makes it different. Each round sharpens the next.
    3. Honest draft. A structured PRD built only from your answers: empty citations, assumptions flagged, and a confidence score on every section.
    4. Validated output. The PRD is checked against a strict schema, then rendered as readable markdown.

    What you get

    Seven sections: problem, personas, scope and non-goals, success metrics, user stories, technical considerations, risks and open questions. Plus:

    • ⚠️ inline flags for every assumption, vague metric, unknown and risk
    • An explicit assumptions list: what to validate first
    • Contradictions found in your own answers
    • Per-section confidence that reflects how much you told it versus how much it assumed

    What's inside

    • SKILL.md: the interview and drafting flow
    • references/synthesizer.md: the PRD-writer prompt and schema
    • scripts/reckoning.mjs: a short, readable validator and renderer with no dependencies (Node 18+)
    • examples/expected-prd.md: a real draft PRD

    Known limitations

    • No web research. Citations stay empty by design; the draft is as good as your answers.
    • Rendering needs Node 18+. Without it, the agent formats the output by hand.
    • Want the draft stress-tested too? Use Reckon (full flow) or Spec Red-Team on the result.

    Free and open source (MIT): github.com/alchemyguy/reckoning

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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