Como usar
- Copie o comando e verifique o pacote antes de instalar no seu ambiente de agente.
- Consulte no original as ferramentas, credenciais e ambientes necessários.
- Descreva os dados de entrada e a entrega esperada; confira a saída com as fontes.
npx skills add https://github.com/magnus919/agent-skills --skill product-shapingAntes de começar
- A instalação não inclui assinatura de modelo, franquia API ou acesso aos seus arquivos.
- Estrelas e instalações indicam atividade, não um teste independente de qualidade ou segurança.
Renderizado do repositório de origem, preservando títulos, exemplos, código, tabelas, links e imagens.
Product Shaping
Pre-commitment methodology for product and engineering work, adapted from Ryan Singer's Shape Up (free edition at 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
- 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").
- 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.
- Patch rabbit holes — attack your own sketch; settle hard decisions now, declare
out-of-bounds cases, cut what the appetite can't afford.
- Write the pitch — problem, appetite, solution, rabbit holes, no-gos.
- Bet — commit the box uninterrupted, downside capped. No finish, no extension by
default: the circuit breaker routes failure back to shaping.
- Build — one integrated slice first, then discovered scopes tracked as
uphill→downhill states; sequence scariest-first; compare down to baseline when deciding to stop.
- Move on — scope cuts are not quality cuts; new feedback needs shaping, not
instant yes.
Reference files
Load only what the current step needs:
| Reference | Load when |
|---|---|
| references/principles.md | You need the why: appetite vs estimate, fixed-time-variable-scope, rough/solved/bounded, evidence boundaries, lineage |
| references/shaping.md | Shaping steps 1–4 in detail, including shaping non-UI/backend/infrastructure work |
| references/betting.md | Bets vs backlogs, circuit breaker mechanics, cycles as optional scaffolding, handling defects between bets |
| references/building.md | Hand-over-responsibility, one-piece-done, scope mapping, hill-state tracking, deciding when to stop |
| references/hybrid-adaptation.md | Any bet involving AI-agent builders: budget currencies, batched steering, verification cost inside scope, kill criteria for non-converging loops |
| references/anti-patterns.md | Before betting anything that matters — documented field failures and their mitigations |
Templates
| Template | Purpose |
|---|---|
| templates/PITCH.md | Fillable five-ingredient pitch document |
| templates/SCOPE_MAP.md | Fillable scope table with hill states, chowder list, and breaker check |
Entry points
| Situation | Start here |
|---|---|
| Raw idea or request arrived | references/shaping.md step 1 |
| Idea is validated but unbounded | references/shaping.md |
| Ready to write up the concept | templates/PITCH.md |
| Deciding what gets the next box | references/betting.md |
| Bet placed, starting the build | references/building.md |
| Builders are AI agents | references/hybrid-adaptation.md |
| Project keeps not finishing / loops won't converge | references/anti-patterns.md, then hybrid-adaptation kill criteria |
When not to use
- The problem itself isn't validated yet →
product-discovery. Shaping narrows
validated problems; it does not investigate whether the problem is real.
- The question is strategic (positioning, market entry, portfolio weight across
quarters) → product-strategy or product-roadmapping-and-portfolio. This skill packages a single bet — one bounded commitment with an appetite and circuit breaker; roadmapping sequences many such bets across cycles with continue/pause/kill criteria.
- The bet is already placed and the work needs a formal spec → `spec-driven-
development` consumes shaped output when formal specification is warranted.
- Comparing unrelated feature proposals by score →
product-methodology(RICE/
MoSCoW). Appetite replaces scoring inside this skill's scope; use one system, not both on the same decision.
- An epic resists decomposition because nobody can define done → route BACK here:
that is an unshaped project, and force-splitting it produces disconnected tasks.
- The work is small, routine, and fully understood — skip shaping overhead; just do
it.
- The bet is placed and you need intent-to-delivery control — classification,
five-field intent contracts, autonomy gating, failure routing, and resumable status across the run. Route to bmad. Shaping ends at the bet; bmad carries the placed intent through bounded, inspectable, resumable agent work.
Related skills
product-discovery— upstream: validates the problem before narrowing beginsproduct-strategy,product-roadmapping-and-portfolio— strategic context above betsproduct-methodology— downstream consumer of a won bet (prioritization, spec drafting)spec-driven-development— optional formal specification of shaped output post-betimplementation-planning,subagent-driven-development— execution after the bet;
decompose only downhill work, never pre-shred a pitch
bmad— intent-to-delivery control-plane protocol once the bet is placed:
classification, five-field intent contracts, autonomy gating, failure routing, resumable spec status
work-tracking— where scope/hill state lives during the buildqa-methodology— edge-case QA as late-cycle level-up, not gate
Evidence note
Every practice claim originates from one company's account (Basecamp, 2019). Independent team records through 2026 show real adaptations and documented abandonments; read references/anti-patterns.md before betting anything that matters, and treat six-week cycles as tunable scaffolding rather than doctrine.
