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Agent skill

Shape

by TheCraigHewitt in TheCraigHewitt/skills

A skill your agent uses when you have a rough product idea and want a complete PRD without sitting through an interactive grilling.

MITAuto-check passedProduct & Project Management

Install Shape

skills CLI
$ npx skills add TheCraigHewitt/skills --skill shape -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install TheCraigHewitt/skills shape --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/TheCraigHewitt/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/coding/shape .claude/skills/shape && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
shape
GitHub stars
157
Token cost
~1.7k tokens
SKILL.md length
735 words
Files
1
Skills in repo
65
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when you have a rough product idea and want a complete PRD without sitting through an interactive grilling.

  • Works in 8 steps: Capture the idea → Explore the codebase → Walk the decision tree → …
  • You have a rough product idea and want a complete PRD without sitting through an interactive grilling
  • SKILL.md covers Pipeline Position, Instructions and Rules
  • Calls gh

What it does

Shape is an agent skill from TheCraigHewitt/skills. Use when you have a rough product idea and want a complete PRD without sitting through an interactive grilling. Claude walks the full decision tree (edge cases, modules, schema, testing, security), self-answers with software-engineering best practices, streams the Q&A live so you can override, and writes the PRD locally with an option to push as a GitHub issue.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Product & Project Management, covering PRD writing and Requirements gathering. It works with GitHub. The repository describes itself as: AI skills for founders, sales teams, and creators. 47 skills across CEO, Sales, YouTube, and General categories. Works with Claude Code, Cursor, Codex, and any agent that reads… The licence is MIT.

When your agent uses it

  • You have a rough product idea and want a complete PRD without sitting through an interactive grilling
  • Tasks that involve PRD writing
  • Tasks that involve Requirements gathering

Example prompts

  • “/shape”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Capture the idea
  2. Explore the codebase
  3. Walk the decision tree
  4. Best-practice defaults
  5. Stream the Q&A live
  6. Write the PRD
  7. Save the PRD locally
  8. Offer to push to GitHub

What it can do on your machine

Read from SKILL.md and the folder at commit fdbf39b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gh

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gh, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Shape loads about 1.7k tokens when it runs. Until then it costs about 92 tokens; SKILL.md has 735 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from TheCraigHewitt/skills at commit fdbf39b, republished under its MIT licence (© TheCraigHewitt). 735 words, ~1,676 tokens.

Download SKILL.mdSave it as .claude/skills/shape/SKILL.md (or your agent's skills folder).
name
shape
description
Use when you have a rough product idea and want a complete PRD without sitting through an interactive grilling. Claude walks the full decision tree (edge cases, modules, schema, testing, security), self-answers with software-engineering best practices, streams the Q&A live so you can override, and writes the PRD locally with an option to push as a GitHub issue.

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

StepCommandWhat It Does
1a/grill-me + /write-a-prdManual path — interactive interview, then PRD
1b/shapeFast path — auto-grill + PRD in one shot
2/prd-to-issuesBreak the PRD into vertical-slice sub-issues
3/ralphImplement 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
Show full SKILL.md (337 more words)Show less
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.

markdown
## 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:

bash
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.

© TheCraigHewitt, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in coding/shape of TheCraigHewitt/skills.

Open the folder on GitHubat commit fdbf39b

Compare with similar skills

Shape next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Shape compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Shape this skillTheCraigHewitt/skills157—~1.7kAutomated safety check: PassMIT
Ouroboros PM InterviewQ00/ouroboros6.2k1 repos~5.7kAutomated safety check: PassMIT
Creating Issuesopsmill/infrahub531—~1.2kAutomated safety check: PassApache-2.0
CCPM Project Managementautomazeio/ccpm8.4k—~1.1kAutomated safety check: PassMIT
Qiaomu AI PRDjoeseesun/qiaomu-ai-prd208—~1.6kAutomated safety check: PassMIT
MVP Product Requirements WriterKhazP/vibe-coding-prompt-template3.1k—~455Automated safety check: PassMIT

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Works with

Categories

Questions about Shape

What does Shape do?

A skill your agent uses when you have a rough product idea and want a complete PRD without sitting through an interactive grilling. Shape is an agent skill from TheCraigHewitt/skills. Use when you have a rough product idea and want a complete PRD without sitting through an interactive grilling.

When should I use Shape?

Shape fits situations like: you have a rough product idea and want a complete PRD without sitting through an interactive grilling; tasks that involve PRD writing; tasks that involve Requirements gathering.

How do I install Shape in Claude Code?

Run `npx skills add TheCraigHewitt/skills --skill shape -a claude-code`. Or copy the skill folder (coding/shape in TheCraigHewitt/skills) into .claude/skills/shape in your project. Claude Code loads it when a task matches its description.

How do I install Shape in Codex?

Run `npx skills add TheCraigHewitt/skills --skill shape -a codex`. Or copy the skill folder (coding/shape in TheCraigHewitt/skills) into .agents/skills/shape in your project. Codex loads it when a task matches its description.

Can I use Shape in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TheCraigHewitt/skills --skill shape -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/shape, .gemini/skills/shape, .github/skills/shape and .opencode/skills/shape in your project.

What does Shape need to run?

Going by SKILL.md and its folder, Shape needs the command-line tools its instructions call (gh).

Does Shape access the network?

SKILL.md contains no URLs. Its commands use gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Shape safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Shape use?

Shape is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Shape use?

About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Shape?

Skills that share tags, products or a category with Shape: Ouroboros PM Interview (Q00/ouroboros, 6.2k stars), Creating Issues (opsmill/infrahub, 531 stars), CCPM Project Management (automazeio/ccpm, 8.4k stars) and Qiaomu AI PRD (joeseesun/qiaomu-ai-prd, 208 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Shape?

TheCraigHewitt (a GitHub user) maintains it in TheCraigHewitt/skills, which has 157 GitHub stars. The repository holds 65 skills in this directory. The repository was last updated on May 22, 2026.

Source: TheCraigHewitt/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.