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Prd Writing

  • 50 installs
  • 76 repo stars
  • Updated August 4, 2026
  • vm0-ai/vm0-skills

Helps with ai & agent building tasks during AI-assisted development.

About

prd-writing is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • prd-writing
  • AI & Agent Building
  • AI-coding skill

Prd Writing by the numbers

  • 50 all-time installs (skills.sh)
  • Ranked #7,245 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/vm0-ai/vm0-skills --skill prd-writing

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Listed on Skillselion
Installs50
repo stars76
Last updatedAugust 4, 2026
Repositoryvm0-ai/vm0-skills

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

Document Architecture

Organize every PRD around these core sections. Adapt the depth of each section to the complexity of the initiative.

The Problem Frame

Ground the entire document in a clearly articulated problem:

  • Identify the specific user pain point in concrete, observable terms
  • Quantify who suffers from this problem and at what frequency
  • Articulate the consequences of inaction: lost revenue, user attrition, operational burden, or competitive exposure
  • Anchor claims in evidence drawn from support tickets, user interviews, behavioral data, or market signals

Desired Outcomes

Translate the problem into 3-5 measurable targets:

  • Frame each outcome around observable change: behavior shifts, efficiency gains, error reduction
  • Separate user-facing outcomes (what improves for the customer) from organizational outcomes (what the business gains)
  • Express outcomes as results rather than deliverables: "cut onboarding duration by half" instead of "redesign the onboarding flow"
  • Every outcome must answer: "what evidence will confirm we achieved this?"

Boundaries and Exclusions

Prevent runaway scope by documenting 3-5 items that are deliberately excluded:

  • Name adjacent capabilities that will not be addressed in this iteration
  • Provide a brief rationale for each exclusion: insufficient data, low leverage, better suited to a follow-up phase, or separate workstream
  • Explicit exclusions protect the team during implementation and set honest expectations with stakeholders

User Narratives

Capture user needs using the pattern: "As a [specific persona], I need [capability] because [underlying motivation]"

Guidance for effective narratives:

  • Personas should be specific enough to guide design tradeoffs ("billing administrator" rather than "user")
  • Describe the desired outcome, not interface mechanics
  • The motivation clause must explain what value the user gains
  • Account for error scenarios, empty states, and edge conditions
  • Represent every distinct persona the feature touches
  • Sequence narratives from highest to lowest priority

Sample narratives:

  • "As a billing administrator, I need to export invoice history by date range because our finance team requires quarterly reconciliation reports"
  • "As a new team member, I need to see a summary of recent project activity because joining mid-project without context slows my contribution"

Characteristics of Strong User Narratives

Apply the INVEST checklist:

  • Independent: Deliverable without coupling to other narratives
  • Negotiable: Implementation details remain flexible
  • Valuable: Produces a tangible benefit for the end user
  • Estimable: Engineering can gauge the approximate effort
  • Small: Completable within a single iteration
  • Testable: Verification criteria are unambiguous

Pitfalls to Avoid in User Narratives

  • Vagueness: "As a user, I want better performance" -- specify which operation and what threshold
  • Dictating implementation: "As a user, I want a modal dialog" -- describe the need, not the widget
  • Missing motivation: "As a user, I want to click save" -- explain the purpose behind the action
  • Oversized scope: "As a user, I want full team management" -- decompose into discrete capabilities
  • Internal framing: "As the backend team, we want to migrate the database" -- this is a technical task, not a user narrative

Requirement Tiers

Tier Classification

Critical (P0): The initiative is incomplete without these. They represent the minimum threshold for solving the stated problem. Litmus test: "If we remove this, does the core problem remain unsolved?" If yes, it stays at P0.

Important (P1): Materially enhances the experience but the fundamental use case functions without them. These are strong candidates for rapid follow-up after initial release.

Deferred (P2): Intentionally excluded from the first version, but the architecture should accommodate them. Recording these prevents design choices that create future obstacles.

Prioritization Discipline

  • Guard P0 ruthlessly. A lean critical set accelerates learning and delivery.
  • When every item is labeled critical, no item is truly critical. Challenge each P0: "Would we genuinely delay release for this?"
  • P1 items should represent near-certain follow-ups, not speculative wishes.
  • P2 items serve as architectural guardrails, shaping design without consuming implementation effort.

The MoSCoW Lens

An alternative classification that maps naturally to stakeholder negotiations:

  • Must have: Without these, the release has no value. Non-negotiable.
  • Should have: Expected by users and important, but the release remains viable without them.
  • Could have: Welcome additions if capacity permits. Omitting them does not delay the timeline.
  • Won't have (this cycle): Explicitly deferred. Documenting these eliminates ambiguity.

Measuring Success

Early Signals (Days to Weeks Post-Launch)

Indicators that shift quickly and reveal immediate reception:

  • Uptake rate: proportion of eligible users who engage with the new capability
  • Activation rate: proportion who complete the primary intended action
  • Completion rate: proportion who accomplish their end-to-end goal
  • Duration: elapsed time for the core workflow
  • Failure rate: frequency of errors, dead ends, or abandoned attempts
  • Return frequency: how often users revisit the capability

Sustained Signals (Weeks to Months Post-Launch)

Indicators that mature over time and reflect lasting impact:

  • Retention lift: measurable improvement in user retention attributable to the feature
  • Revenue contribution: driven upgrades, expansions, or new bookings
  • Satisfaction shift: movement in NPS, CSAT, or qualitative sentiment
  • Support load reduction: decrease in related support inquiries
  • Win-rate influence: improvement in competitive deal outcomes

Establishing Targets

  • Targets must be precise: "60% uptake within the first 14 days" rather than "strong adoption"
  • Derive targets from analogous launches, industry norms, or stated hypotheses
  • Define both a baseline expectation and a stretch aspiration
  • Specify the measurement instrument: which tool, which query, which time window
  • Schedule evaluation checkpoints: one week, one month, one quarter after launch

Verification Criteria

Express acceptance criteria using structured conditions or checklists.

Structured Conditions:

  • Given [starting state or precondition]
  • When [user action]
  • Then [expected system behavior]

Example:

  • Given the organization has enabled single sign-on
  • When an employee navigates to the login screen
  • Then the system redirects them to the organization's identity provider

Checklist Approach:

  • [ ] Administrators can configure the identity provider URL in workspace settings
  • [ ] Team members see a branded sign-on option on the login screen
  • [ ] First-time SSO authentication provisions a new account automatically
  • [ ] SSO authentication links to an existing account when the email matches
  • [ ] Authentication failures surface a descriptive error message

Writing Effective Verification Criteria

  • Cover the primary path, error conditions, and boundary scenarios
  • Describe observable behavior, not internal implementation
  • Include negative cases: what should explicitly not occur
  • Each criterion should be independently verifiable
  • Replace subjective language ("responsive", "intuitive", "seamless") with concrete thresholds

Scope Governance

Indicators of Scope Expansion

Watch for these warning signs:

  • Requirements surface after the specification is finalized
  • Incremental additions compound into a substantially larger effort
  • The team builds capabilities that no user requested ("since we are already in there...")
  • Target dates shift without a deliberate re-scoping conversation
  • Stakeholders append requirements without corresponding removals

Containment Strategies

  • Anchor every specification with explicit exclusions
  • Enforce a tradeoff rule: new scope additions require a corresponding removal or timeline adjustment
  • Maintain a clear boundary between the current iteration and subsequent phases
  • Periodically verify that every requirement traces back to the stated problem
  • Apply time caps to exploratory work: "if we cannot resolve X within two days, we defer it"
  • Maintain a "future ideas" backlog for worthy suggestions that fall outside the current scope

Unresolved Questions

Every PRD should track open items:

  • Record questions that require resolution before or during implementation
  • Assign each question to a responsible party: engineering, design, legal, data science, or a specific stakeholder
  • Classify questions as blocking (must resolve before work begins) or non-blocking (can resolve in parallel with implementation)

Timing and Sequencing

  • Document hard deadlines: contractual obligations, external events, regulatory milestones
  • Identify cross-team dependencies and their expected delivery dates
  • Recommend phasing if the initiative exceeds a single release cycle

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