Shape — Auto-Grill to PRD

Take a rough product idea and turn it into a complete PRD in one shot. No interactive grilling — Claude walks the decision tree itself, answers each question with software-engineering best practices, streams the Q&A live so you can spot bad assumptions, and writes the PRD.

Use /shape when you trust Claude's judgment and want speed. Use /grill-me + /write-a-prd when you want hands-on control over every decision.

Pipeline Position

Step	Command	What It Does
1a	/grill-me + /write-a-prd	Manual path — interactive interview, then PRD
1b	/shape	Fast path — auto-grill + PRD in one shot
2	/prd-to-issues	Break the PRD into vertical-slice sub-issues
3	/ralph	Implement each sub-issue autonomously with TDD + code review

shape produces the same PRD format as write-a-prd, so /prd-to-issues and /ralph consume its output without changes.

Instructions

When the user invokes this skill:

1. Capture the idea

If the user passed an idea as an argument, use it. Otherwise ask once:

What do you want to build? (one paragraph is fine)

Then proceed without further interactive questions until step 8.

2. Explore the codebase

Before answering anything, ground your decisions in reality:

• Read README.md, CLAUDE.md, and any architecture docs
• Identify existing modules, conventions, test patterns, and prior art the feature should match
• Verify any factual assertions in the user's idea — don't trust them, check
• Note the language, framework, test runner, and directory layout

If there is no codebase (empty directory or greenfield), skip to step 3 and record this in the PRD's Further Notes.

3. Walk the decision tree

For each branch below, generate the questions a thorough engineer would ask, then answer each one yourself. Do not skip a branch even if it feels obvious — that is the entire point of this skill.

• Actors & user stories — who uses this, what they want, what success looks like
• Happy-path flow — primary interaction step by step
• Edge cases — empty inputs, large inputs, concurrent access, partial failures, network errors, permission denied, missing data, unicode/encoding, time zones
• Data model & schema — entities, relationships, indexes, migrations
• Module boundaries — deep modules, public interfaces, what stays internal
• API contracts — request/response shapes, error codes, idempotency, versioning
• Testing strategy — what to test, what to mock (only at boundaries), prior art in the repo
• Security — authn/authz, input validation, secrets, rate limiting
• Observability — what to log, what to surface as metrics
• Out of scope — explicit non-goals to prevent scope creep
• Dependencies & blockers — what must exist first

4. Best-practice defaults

When self-answering, prefer:

• Boring over clever — simple, well-understood patterns
• Deep modules (Ousterhout) — wide functionality behind a simple, stable interface
• Match the codebase over external standards — project conventions win
• TDD-friendly design — testable through public interfaces, not internals
• Validate at system boundaries — trust internal callers, fail loudly at the edge
• YAGNI — no speculative abstractions, no features the user didn't ask for
• Parameterized queries, never string concatenation
• Rate limit auth endpoints
• Never log secrets, tokens, or PII
• Mock only at system boundaries (external APIs, DBs, time, randomness, filesystem) — never mock internal collaborators

Codebase facts always beat generic best practices. If the project already does X, the answer is X.

5. Stream the Q&A live

For every decision, emit a block in this exact format as you make the call — do not batch:

Q: <the question>
A: <the chosen answer>
Why: <one sentence — cite a codebase reference if relevant>

This is the user's chance to spot a bad assumption early.

6. Write the PRD

Use this template exactly. It matches /write-a-prd, so the rest of the pipeline accepts it unchanged.

## Problem Statement

The problem the user is facing, from the user's perspective.

## Solution

The solution, from the user's perspective.

## User Stories

A long, numbered list:
1. As a <actor>, I want a <feature>, so that <benefit>

Cover every aspect of the feature surfaced in your decision tree.

## Implementation Decisions

- Modules to build or modify
- Public interfaces of those modules
- Architectural decisions
- Schema changes
- API contracts
- Specific interactions

Do NOT include file paths or code snippets — they go stale fast.

## Testing Decisions

- What makes a good test here (test external behavior, never implementation details)
- Which modules will be tested
- Prior art for the tests (similar patterns already in the codebase)

## Out of Scope

Explicit non-goals.

## Further Notes

Anything else worth recording.

## Decisions Log

Every Q/A/Why block from step 5, in the order they were decided.

7. Save the PRD locally

• Generate a kebab-case slug from the idea (e.g. "rate-limited /healthz endpoint" → rate-limited-healthz-endpoint)
• Create ./prds/ if it doesn't exist
• Write the PRD to ./prds/<slug>.md
• Print the absolute path

8. Offer to push to GitHub

After saving, ask the user once:

Push this as a GitHub issue? [y/N]

On y, run:

gh issue create --title "<slug>" --body-file ./prds/<slug>.md

Print the issue URL.

On n or no answer, stop. The local file is enough — the user can push later.

Rules

• Don't ask the user questions during the decision tree. The whole point is auto-answering. The only interactive moments are: capturing the idea (if not given) and the GitHub push prompt at the end.
• Don't skip branches. Even trivial-feeling branches get walked — completeness is the value.
• Codebase facts beat generic best practices. If the project already does X, X is the answer.
• No speculative scope. If the user didn't ask for it and the codebase doesn't require it, it goes in Out of Scope.
• The PRD template is fixed. It must match /write-a-prd exactly so /prd-to-issues and /ralph keep working.