prd-methodology

分类: 开发与编程 | 上传者: geckse | 下载: 0 | 版本: v1.0（最新）

PRP (Product Requirement Prompt) methodology for writing PRDs. Reference for best practices in structuring requirements documents for coding agents. --- # PRP Methodology — Quick Reference The PRP (Product Requirement Prompt) framework is a structured process for creating PRDs that coding agents can execute in a single pass. ## Core Principle A PRD must contain ALL context needed for implementation. If a fresh Claude session with only the PRD can't build the feature correctly, the PRD is incomplete. ## The 3-Step Process 1. **Write initial description** — Brain dump what you want: feature, tech stack, constraints, integrations, examples, documentation references 2. **Generate the PRD** — Research the codebase + web, interview the user, produce a structured document following the base template 3. **Execute the PRD** — Clear context, start fresh, implement from the PRD alone ## What Makes a Good PRD **DO:** - Reference specific files and code patterns from the codebase - Write testable validation criteria ("returns 401 on invalid token") - Include explicit non-goals to prevent scope creep - List anti-patterns specific to the project - Order implementation steps by dependency (what must exist before what) - Include migration strategy for existing data/behavior **DON'T:** - Use vague validation criteria ("works well", "is performant") - Leave technical design abstract ("use appropriate data structures") - Assume the implementing agent knows project conventions — spell them out - Skip the non-goals section — agents will over-build without boundaries - Write steps that can't be verified independently ## Interview Technique The most valuable part of PRD generation is the interview. Goal: reduce assumptions to near zero. - Ask at least 8-10 questions before writing - Batch questions in groups of 3-4 - Provide recommended answers based on codebase research - Cover: scope, users, technical constraints, data model, compatibility, edge cases, testing, anti-patterns - Final ques

更新日志: Source: GitHub https://github.com/geckse/markdown-vdb