PM PRD Development

SkillDev tools

Turn discovery context into a clear PRD with problem framing, scope boundaries, requirements, and success criteria.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the PM PRD Development skill

What this skill tells your AI

The instructions your AI receives, as published by contextgo/contextgo in src/process/resources/skills/pm-workbench-pack/skills/pm-prd-development/SKILL.md and read by ahel’s review.

Create a product requirements document that earns engineering trust and stakeholder clarity.

What a good PRD does

A strong PRD explains:

  • what problem matters
  • for whom it matters
  • why now
  • what the proposed solution is
  • how success will be measured
  • what is in scope and out of scope
  • what remains uncertain

A PRD is not a giant dump of every idea the team discussed.

Use when

  • Discovery has produced enough confidence to propose committed work.
  • Engineering needs a durable decision document instead of scattered chat context.
  • A major initiative needs alignment on scope, metrics, and tradeoffs.

Do not use when

  • The team still has not validated the problem.
  • The change is tiny and can be captured in a lightweight task or story.
  • Stakeholders only want a concept note or option memo, not a committed requirements document.

Anti-patterns

  • Writing the solution section before the problem section is credible
  • Hiding uncertainty instead of listing open questions
  • Mixing nice-to-have ideas into required scope
  • Turning the PRD into a UI spec or implementation spec
  • Omitting metrics and then calling the work "strategic"

PRD structure

1. Executive summary

One short paragraph:

  • user or segment
  • problem
  • proposed approach
  • expected outcome

2. Problem framing

Document:

  • target user
  • current pain or failure state
  • evidence
  • business consequence

Use direct evidence where possible:

  • analytics signal
  • interview quote
  • support pattern
  • revenue or operational impact

3. Why now

Explain urgency without hype:

  • strategic timing
  • market or customer pressure
  • operational cost of waiting
  • dependency on upcoming work

4. Solution overview

Describe the proposed approach at the right altitude:

  • core user flow or job-to-be-done change
  • primary surfaces or systems involved
  • important non-goals

Do not over-specify UI details unless they affect the decision itself.

5. Success metrics

Always include:

  • primary metric
  • baseline
  • target
  • leading indicators
  • guardrails

Guardrails matter. Avoid "win one metric while breaking another."

6. Requirements

Split requirements into clear buckets:

  • user needs
  • functional requirements
  • operational or policy constraints
  • edge cases and failure handling

Write requirements in plain language first. Add acceptance criteria when precision matters.

7. Scope boundaries

Include:

  • in scope
  • explicitly out of scope
  • assumptions this PRD depends on

This is where you stop scope creep before it starts.

8. Dependencies and risks

List:

  • upstream teams or systems
  • technical enablers
  • rollout constraints
  • risk and mitigation

9. Open questions

A PRD with no open questions is usually dishonest.

List only the unresolved issues that can still change scope, architecture, launch, or measurement.

PRD writing workflow

Step 1: inventory the raw inputs

Collect the current source material:

  • discovery notes
  • stakeholder asks
  • analytics snapshots
  • design concepts
  • engineering constraints

If the input set is thin, say that the PRD is provisional.

Step 2: write the problem and metric sections first

If these sections stay weak, the solution section will be misleading.

Step 3: describe the solution and boundaries

Keep the solution tied to the problem. Every major scope item should map back to a user pain, strategic requirement, or measurement need.

Step 4: pressure-test the document

Ask:

  • Could engineering tell what matters most?
  • Could a stakeholder tell what is not included?
  • Could someone six weeks later understand why this exists?
  • Would failure be measurable?

Step 5: finalize with explicit uncertainty

Tag uncertain areas as:

  • discovery follow-up
  • design decision
  • technical investigation
  • policy or go-to-market dependency

Output format

Return the PRD with these headings:

  • Executive Summary
  • Problem Statement
  • Target Users
  • Why Now
  • Solution Overview
  • Success Metrics
  • Requirements
  • In Scope / Out of Scope
  • Dependencies and Risks
  • Open Questions

Quality bar

The PRD is strong only if:

  • the problem statement could survive skeptical review
  • the metric section defines success clearly
  • out-of-scope items are explicit
  • open questions are honest and limited
  • the document enables execution without pretending all uncertainty is gone

Use together with

  • pm-discovery-process before drafting
  • pm-roadmap-planning after the initiative is ready to be sequenced with other work

Signals

GitHub stars
54
Forks
5
Last commit
May 2026
Advanced
Catalog kind
skill
Gateway key
pm-prd-development
Source
github.com/contextgo/contextgo