Product PRD

Author the right product doc for the work (sometimes a 3-line ticket, sometimes a full PRD), never more than the work warrants. This skill writes no application code; it produces the requirements a build (implement-feature) then works from. Output lands under docs/specs/prd/. <skill-dir> below is this skill's directory.

Input

$ARGUMENTS

Parse the source (first match wins), then read it:

A trailing --tier brief|one-pager|big and/or --intent validation|execution overrides the assessment.

Prerequisites & fallback

Parallel research and discovery use the Task tool with Explore/haiku subagents. No Task tool? Run every research and discovery step inline, sequentially: the phase → gate → phase structure below is the workflow; subagents are just how it parallelizes.

Lean by default

The organizing principle. Default to a single docs/specs/prd/PRD.md and split a section into its own file only when it outgrows itself. Length is not quality: a bloated PRD and a tight one get rated worlds apart on content alone. Cut anything that doesn't trace back to the problem, a goal, or a success metric.

• Track position with a single Phase: X line in your working notes: no per-turn counters, no resume state.
• Cost stop-condition: if the work seems to want a large multi-file tree, stop and ask before emitting it. Never auto-generate a 12- or 37-file document set. That tree exists only behind <skill-dir>/scripts/scaffold.py --enterprise <tier>, for a platform-scale program that has genuinely outgrown one file.

Tiers: size AND intent

Gate-zero decides whether to write a doc; the tier decides which doc. Full detail: references/phase-workflow.md.

Graduating guard: if a one-pager draft exceeds ~5-7 requirements or the scope touches more than one team/system, stop and restart in prd-full.md rather than bloating the one-pager in place.

Workflow

Four phases: Discover → Decide → ═authorization gate═ → Author → Validate.

Phase: Discover

Read the input source. If the repo is relevant (existing product), inspect it before asking the user anything: spawn an Explore/haiku agent (or do it inline):

Task (Explore, haiku): "Discover this repo's product surface & stack: read CLAUDE.md/AGENTS.md, README,
package/build files; map major components, data model, existing capabilities, and any current PRD/specs
under docs/. Return a structured summary, each finding tagged CONFIRMED | INFERRED | UNKNOWN."

Tag every finding CONFIRMED / INFERRED / UNKNOWN: never present an inference as a fact. Pick the discovery mode by context: cold start → 3-5 lettered clarifying questions; warm start → synthesize from the conversation + a quick repo scan, then run a lightweight gap check.

Gate-zero: does this even need a written doc? For a one-line change, a bug-shaped fix, or anything faster to prototype than to spec, say so and stop:

"This doesn't need a PRD. Here's a 3-line ticket: {problem / change / acceptance}, or just prototype it and we'll spec from what we learn."

Being willing to talk the user out of a doc is the point of gate-zero.

Phase: Decide

1. Pick the tier: assess size, then branch the big tier on intent (validation vs execution). Honor --tier/--intent if passed. State the choice and why in one line.
2. Research: fan out one Explore/haiku agent per workstream the open decisions actually need (competitors, technical options, regulatory, platform, accessibility). Each returns rows finding | source URL | date | confidence | implication and invents nothing. Merge them as finding rows in the one decision log (assets/templates/decision-log.md). Cite every externally-derived claim.
3. Interview: ask the open decisions in dependency order (vision → problem → users → scope → journeys → architecture → non-functional → metrics), each via AskUserQuestion with the decision-question.md template (decision, evidence, a recommendation with rationale, alternatives). Record answers as decision/assumption/question rows in the same log. Keep facts, assumptions, and recommendations separate: a recommendation never hardens into a requirement without an approved decision. For the users decision, capture persona and user evidence with product-design-spec's persona.md rulebook (via the Skill tool where available, else read persona.md from product-design-spec's assets/templates/) rather than duplicating persona guidance here.

4. Alignment gate (authorization): assemble the ~1-page alignment-summary.md and present it:

   "Alignment summary for {product}: tier = {tier}, {N} approved decisions, {M} assumptions, {K} open. Do you authorize me to author docs/specs/prd/PRD.md?"

   Stop here if the answer is no: revise and re-present. Author nothing before authorization.

Phase: Author

Create the single file, then fill it from the tier template:

python <skill-dir>/scripts/scaffold.py --dir docs/specs/prd   # one PRD.md

• Requirements use assets/templates/requirement.md: a unique ID (PRD-<CAT>-NNN, six categories FR/NFR/UX/SEC/DATA/DES), RFC-2119 language, one behaviour per requirement, a 3-field evidence block (finding / evidence path / confidence), and Given/When/Then acceptance criteria. Rules: references/requirement-hygiene.md (the shared rulebook) and references/requirement-standards.md.
• Non-goals are mandatory at medium+ and stated POSITIVELY: say where the excluded work lives or when it's revisited, never a bare "we won't do X" (a downstream agent can't infer scope from omission).
• Tag every unresolved gap [NEEDS CLARIFICATION: ...] rather than guessing: it stays greppable.
• Prioritization/metrics (JTBD/Kano/MoSCoW/RICE, NSM/HEART/AARRR) are opt-in: reach for references/frameworks.md only when finer granularity is actually wanted.
• Diagrams: delegate Mermaid to the docs-diagram skill (via the Skill tool where available, otherwise apply its diagram conventions inline). Task breakdown once requirements exist: hand off to project-planner. A decision worth a permanent record: offer docs-adr (made) / docs-rfc (proposed).

Phase: Validate & hand off

python <skill-dir>/scripts/validate.py --dir docs/specs/prd   # gate: 0 CRITICAL, 0 MAJOR
python <skill-dir>/scripts/hygiene.py  --dir docs/specs/prd   # advisory INVEST/EARS lints

Fix every CRITICAL/MAJOR (missing/duplicate IDs, ACs without Given/When/Then, missing Non-Goals, unresolved [NEEDS CLARIFICATION], compound requirements, dangling links, leftover placeholders). Then:

• Self-grade inline (no separate report file): does every requirement trace to a stated goal? Check for vague wording and missing sections, and confirm no requirement still bundles more than one behaviour. State the readiness verdict in a sentence or two.
• Hand off: write the file to its repo path (report the path), or, if the user works in a tracker, offer to open the ticket/issue. Name the downstream consumer: product-design-spec (design) and implement-feature (build).

AI-agent-consumer mode (optional)

When the PRD's downstream reader is an AI implementation agent (this repo's own implement-feature/fix-bug) rather than a human, switch modes. Use headings + lists over prose; state every non-goal positively; give every requirement an independently-testable acceptance criterion. Optionally emit the companion assets/templates/agent-contract.md. It pairs exact commands (with flags) with an Always / Ask-First / Never boundary list, then separately records the project's own conventions.

Anti-hallucination

• Investigate the repo and search the web before asking the user: don't ask what the code already answers.
• Tag every finding CONFIRMED / INFERRED / UNKNOWN; never present an inference or a recommendation as a fact or an approved requirement.
• Every externally-derived claim carries a source. No fabricated counts or metrics, and no invented competitor data.
• Never invent requirement IDs that don't trace to a decision or need. Run validate.py before declaring done.
• The alignment gate is real: author files only after explicit authorization.

References

• references/phase-workflow.md: the four phases, gate-zero, size+intent tiering, graduating guard, research fan-out
• references/requirement-hygiene.md: RFC-2119, the 8-term vague blocklist, INVEST, EARS, compound-split, [NEEDS CLARIFICATION] (shared with product-design-spec)
• references/requirement-standards.md: the six-category ID scheme, requirement quality, the one decision log
• references/frameworks.md: opt-in prioritization (JTBD/Kano/MoSCoW/RICE) & metrics (NSM/HEART/AARRR) pipelines
• assets/templates/: brief, one-pager, prfaq, prd-full, requirement, decision-question, decision-log, alignment-summary, agent-contract, prd-root
• scripts/scaffold.py · scripts/validate.py · scripts/hygiene.py

Boundaries

• The design half (IA, flows, screens, states) → product-design-spec.
• The visual token system (DTCG / DESIGN.md) → product-design-tokens.
• A single architecture/decision record → docs-adr (records a made decision) or docs-rfc (proposes one).
• A lightweight spec that immediately precedes coding → implement-feature.
• Auditing an existing design's UX → review-design. Rendering visual assets → codex-imagegen.
• WHAT/WHY only, never HOW. Writes no application code.