product-shaping SKILL.md skillA

product-shaping from magnus919/agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add magnus919/agent-skills/product-shaping@git:20260824.e10508b

Pins git:20260824.e10508b in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
magnus919/agent-skills
Path
product-shaping/SKILL.md
Versions recorded
3
Latest version
git:20260824.e10508b, committed Aug 24, 2026
First version recorded
Aug 23, 2026
Size
7,439 bytes
Repository stars
166
License
MIT

Use this skill to shape product or engineering work before committing time to it: set appetites instead of estimates, narrow raw ideas into bounded problems, sketch solutions at the right level of abstraction, de-risk rabbit holes, write pitches, bet with capped downside (circuit breaker), and govern builds with discovered scopes and scope hammering. Adapted from Basecamp's Shape Up and extended for human+AI-agent teams. Use when a raw idea, feature request, or "redesign X" grab-bag needs to…

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# Product Shaping

Pre-commitment methodology for product and engineering work, adapted from Ryan Singer's
*Shape Up* (free edition at [basecamp.com/shapeup](https://basecamp.com/shapeup)),
extended for teams whose builders include AI agents.

The loop: **shape** a raw idea into a bounded pitch → **bet** a fixed appetite on it →
**build** by discovering scopes and hammering scope to fit the box → **move on**,
letting post-ship feedback re-enter as raw ideas.

## The core moves

1. **Set boundaries** — choose the appetite ("how much is this worth?") and narrow the
   problem to one specific story. Kill grab-bags ("redesign X", "X 2.0").
2. **Find the elements** — sketch the solution rough, solved, and bounded: breadboards
   for flows, fat-marker fidelity for visual problems, components-and-contracts for
   non-UI work.
3. **Patch rabbit holes** — attack your own sketch; settle hard decisions now, declare
   out-of-bounds cases, cut what the appetite can't afford.
4. **Write the pitch** — problem, appetite, solution, rabbit holes, no-gos.
5. **Bet** — commit the box uninterrupted, downside capped. No finish, no extension by
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add magnus919/agent-skills/product-shaping@sha256:086d41b5e1933d9b

The line at the top of this page pins the label git:20260824.e10508b, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_ldisim5nwgukelqh.svg)](https://markdownregistry.com/a/art_ldisim5nwgukelqh)

4 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 3 versions of this file, between Aug 23, 2026 and Aug 24, 2026, more than one a day.

versioncommittedcommitsizeaudit
git:20260824.e10508b latest2026-08-24 e10508b 7,439 BA view · diff
git:20260823.c0412b52026-08-23 c0412b5 6,940 BA view · diff
git:20260823.673335d2026-08-23 673335d 6,815 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (7439 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

magnus919/agent-skills · 166 stars · license MIT · pushed 2026-11-04 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_ldisim5nwgukelqh
GET https://markdownregistry.com/api/v1/resolve?ref=magnus919/agent-skills/product-shaping
GET https://markdownregistry.com/api/v1/blob/086d41b5e1933d9b10c389325c6914403fba9f54a375797b902c9a404e9a0cd2

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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