Receber por email
← Voltar para o catálogo

prompt

Extract structured requirements (F-xx) from user input. Outputs JSON to .copilot-tracking/

16estrelas
Atualizado há 7 meses

Ver no GitHub ↗ Licença: NOASSERTION

Como adicionar

/plugin marketplace add Roberdan/convergio-community

O comando exato pode variar conforme o repositório. Confira o README no GitHub.

Para o autor da skill

Cole no README do seu repo

Mostra que sua skill está catalogada na Skillteca, gera backlink e tráfego rastreável.

[![Skillteca](https://www.skillteca.com.br/api/badge/prompt-roberdan/svg)](https://www.skillteca.com.br/skills/prompt-roberdan)
#ai

Alerta por categoria

Receba novas skills de Design e Frontend toda segunda

1 email curto, só com as skills novas de Design e Frontend. 4 minutos de leitura, sem spam, cancela com 1 clique.

Você confirma o email no primeiro envio. Sem spam. Cancela com 1 clique.

Ler descrição completa

Prompt Translator Skill

Reusable workflow extracted from prompt agent expertise.

Purpose

Extract structured functional requirements (F-xx) from natural language user input, producing machine-readable JSON for downstream planning agents.

When to Use

  • New feature requests that need structured decomposition
  • Ambiguous user input requiring clarification before planning
  • Requirements extraction before @planner execution
  • Any input that needs F-xx requirement mapping

Workflow Steps

  1. Context Gathering
  2. Read repository state via git-digest.sh
  3. Understand project structure and existing patterns
  1. Clarification (MANDATORY)
  2. Identify ambiguities in user input
  3. Ask about: scope, negative requirements, edge cases, priority
  4. NEVER fill gaps with assumptions — ask or mark TBD
  1. Requirement Extraction
  2. Extract EVERY requirement (explicit + implicit) as F-xx
  3. Use EXACT user words — NEVER paraphrase
  4. Each requirement needs: id, said (verbatim), verify (machine-checkable), priority
  1. Output Generation
  2. Save to .copilot-tracking/prompt-{NNN}.json
  3. Include: objective, user_request, requirements[], scope, stop_conditions
  1. User Confirmation
  2. Ask "Have I captured everything? Anything missing?"
  3. User confirms → offer handoff to @planner

Inputs Required

  • User request: Natural language description of desired feature/change
  • Repository context: Auto-detected from current working directory

Outputs Produced

  • Prompt JSON: .copilot-tracking/prompt-{NNN}.json with structured F-xx requirements
  • Handoff: Ready for @planner to create execution plan

Output Format

{
  "objective": "one sentence goal",
  "user_request": "EXACT user words, verbatim",
  "requirements": [
    { "id": "F-01", "said": "exact words", "verify": "how to check", "priority": "P1" }
  ],
  "scope": { "in": ["included"], "out": ["explicitly excluded by user"] },
  "stop_conditions": ["All F-xx verified", "Build passes", "User confirms"]
}

Critical Rules

| Rule | Requirement | | --------- | ----------------------------------------------------------------------- | | said | EXACT user words, never paraphrase | | verify | Machine-checkable (grep, test command, build passes), not prose | | scope.out | ONLY items USER explicitly said to exclude, NEVER add on own initiative | | Purpose | This JSON is read by planner agent to generate spec.json |

Related Agents

  • po-prompt-optimizer - Prompt engineering and optimization
  • strategic-planner - Strategic planning from requirements
  • ali-chief-of-staff - Orchestration and delegation
Compartilhar X LinkedIn