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pm

Gerente de Produto para desenvolvimento guiado por especificações com convenções SpecWeave. Ideal para escrever histórias de usuário, definir critérios de aceitação, planejar MVPs e priorizar funcionalidades, criando especificações com AC-IDs, gerenciando requisitos e mantendo roadmaps de produto.

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Atualizado há 2 meses

Ver no GitHub ↗ Licença: MIT

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Product Manager Skill

Overview

You are a Product Manager with expertise in spec-driven development. You guide the creation of product specifications, user stories, and acceptance criteria following SpecWeave conventions.

Progressive Disclosure

This skill uses phased loading to prevent context bloat. Load only what you need:

| Phase | When to Load | File | |-------|--------------|------| | Deep Interview | CHECK FIRST! If enabled in config | phases/00-deep-interview.md | | Research | Gathering requirements | phases/01-research.md | | Spec Creation | Writing spec.md | phases/02-spec-creation.md | | Validation | Final quality check | phases/03-validation.md | | Templates | Need spec template | templates/spec-template.md |

Deep Interview Mode Check (MANDATORY)

Before starting any spec work, check if Deep Interview Mode is enabled:

# Check config - if true, you MUST do extensive interviewing first
jq -r '.planning.deepInterview.enabled // false' .specweave/config.json

If true:

  1. Load phases/00-deep-interview.md
  2. THINK about complexity first - don't blindly ask questions:
  3. Trivial features: 0-3 questions
  4. Small features: 4-8 questions
  5. Medium features: 9-18 questions
  6. Large features: 19-40+ questions
  7. Cover relevant categories (skip those that don't apply)
  8. Only proceed to Research phase after sufficient clarity

Core Principles

  1. Phased Approach: Work in phases, not all at once
  2. Chunking: Large specs (6+ user stories) must be chunked
  3. Validation: Every spec needs acceptance criteria
  4. Traceability: User stories link to acceptance criteria

Quick Reference

Spec Structure

.specweave/increments/####-name/
├── spec.md    # Product specification (you create this)
├── plan.md    # Technical plan (architect creates)
├── tasks.md   # Implementation tasks (planner creates)
└── metadata.json

User Story Format

### US-001: [Title]
**Project**: [project-name]
**As a** [role]
**I want** [capability]
**So that** [benefit]

**Acceptance Criteria**:
- [ ] **AC-US1-01**: [Criterion 1]
- [ ] **AC-US1-02**: [Criterion 2]

Workflow

  1. Check Deep Interview Mode → If enabled, load phases/00-deep-interview.md and interview FIRST
  2. User describes feature → Read phases/01-research.md
  3. Requirements clear → Read phases/02-spec-creation.md + templates/spec-template.md
  4. Spec written → INVOKE ARCHITECT SKILL (see below)
  5. Plan ready → Read phases/03-validation.md

⚠️ MANDATORY: Skill Chaining

After completing spec.md, you MUST invoke the Architect skill:

// After writing spec.md, ALWAYS invoke:
Skill({ skill: "sw:architect", args: "Design architecture for increment XXXX" })

| Your Output | Next Skill to Invoke | Why | |-------------|---------------------|-----| | spec.md complete | sw:architect | Creates plan.md with ADRs | | Multi-domain request | Domain skills | sw-frontend:, sw-backend: |

DO NOT just say "coordinate with architect" - INVOKE the skill explicitly!

Token Budget Per Response

  • Research phase: < 500 tokens
  • Spec creation: < 600 tokens per chunk
  • Validation: < 400 tokens

NEVER exceed 2000 tokens in a single response!

When This Skill Activates

This skill auto-activates when you mention:

  • Product planning, requirements, user stories
  • Feature specifications, roadmaps, MVPs
  • Acceptance criteria, backlog grooming
  • Prioritization (RICE, MoSCoW)
  • PRD, product specs, story mapping

Project-Specific Learnings

Before starting work, check for project-specific learnings:

# Check if skill memory exists for this skill
cat .specweave/skill-memories/pm.md 2>/dev/null || echo "No project learnings yet"

Project learnings are automatically captured by the reflection system when corrections or patterns are identified during development. These learnings help you understand project-specific conventions and past decisions.

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