skills/product-requirements-doc/SKILL.md
Optional PRD methodology — loaded by the questioner agent when a feature request is vague or complex enough to warrant a structured product spec alongside task.md. Produces a PRD artifact that downstream design-author work can ground decisions in.
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A PRD translates a vague or complex feature request into a structured artifact
that complements task.md. The questioner produces it when intent is rich
enough to need explicit scope, acceptance criteria, and constraints, rather
than a one-page task summary alone.
The goal is precision, not exhaustive documentation: clear scope, unambiguous acceptance criteria, and explicit boundaries that prevent scope creep when the design-author later turns the task into an approach.
The questioner produces a PRD (in addition to the standard task.md
and questions.md) when the feature request is:
For simple, well-scoped requests ("add a --verbose flag to the CLI"), the
standard task.md is sufficient — no PRD needed.
Write the PRD to docs/plans/<id>/prd.md. Reference its path from
task.md so the design-author knows to read it.
One to three sentences: what problem does the user have? Why does it exist? Why does it matter to solve it now? Ground every subsequent section in this.
Enumerate the user workflows the feature must support. Use this format:
As a [user type], I want to [action], so that [outcome].
Every user story that is in scope gets listed. User stories that are explicitly out of scope get listed in Non-Goals. Stories that might be in scope later get listed in Future Scope.
Keep stories at the "what" level, not the "how" level. "As a developer, I want to see syntax errors highlighted in the editor" is a story. "As a developer, I want the parser to return an AST node with error metadata" is an implementation detail.
For each user story, define the conditions that prove it is implemented correctly. Acceptance criteria are written as verifiable statements:
GIVEN [initial context]
WHEN [user action]
THEN [expected outcome]
Or as a checklist when the story is simple:
- [ ] The user can do X without doing Y first
- [ ] Doing X with invalid input shows error message Z
- [ ] Doing X is reflected in the audit log within 1 second
Acceptance criteria must be:
Explicit statement of what is and is not in scope.
In Scope:
Out of Scope:
Future Scope:
Non-negotiable requirements the implementation must satisfy:
When the design-author finds a PRD path referenced in task.md, it should:
When the structure-planner reads the design, the PRD's acceptance criteria become the source of vertical-slice acceptance tests.
data-ai
Todo-first progress convention for multi-step procedures — loaded by every multi-step agent to track its own steps without drift
testing
Adversarially review a technical design document with fresh context before the human gate. Dispatches the built-in `general-purpose` subagent (clean context, no shared history with the design-author) against `docs/plans/<id>/design.md` and presents its verdict — APPROVE, REQUEST CHANGES, or COMMENT. Optional, not part of the QRSPI pipeline. Trigger on "review the design doc", "audit design.md", "is this design ready", or `/eng-design-doc-review`.
development
Generator-evaluator separation and review methodology — loaded by review agents to enforce fresh-context review discipline, Conventional Comments format, and gate verdicts
data-ai
Prepare one or more isolated git worktrees — one per repository the topic touches. Router action — no agent. Trigger on "set up the worktree", "isolate this work", or "/team-worktree".