prd-writing-toolkit

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SUMMARY

AI PRD generation, PRD review, and Feishu/Lark collaboration workflows for B2B product management and system design.

README.md

PRD Writing Toolkit

AI PRD generation, PRD review, and Feishu/Lark collaboration workflows for B2B product management and system design.

中文简介:这是一套面向 B 端产品经理的 AI Native 工具链,把 写 PRD、审 PRD、在飞书里协作收口 串成一个真正可落地的闭环。

PRD Writing Toolkit is designed for teams that want more than a single prompt file. It turns product writing and review into a repeatable operating system:

  • AI PRD generation for turning raw context into structured drafts
  • PRD review for catching gaps, contradictions, and risk before handoff
  • Feishu/Lark collaboration for writing comments back, collecting decisions, and controlling a real delivery gate
  • B2B product management and system design workflows that respect complexity instead of forcing every requirement into the same template

Origins & Credits

This toolkit is an integrated workflow product, but it does not erase where the core upstream skill work came from.

Huge thanks to pmYangKun for creating and open-sourcing the original create-prd and check-prd skill repositories. PRD Writing Toolkit extends those foundations into a fuller end-to-end workflow with a vendored quality framework and a Feishu/Lark delivery gate.

Who This Is For

  • Product managers writing B2B PRDs, solution specs, and internal system proposals
  • AI-native PM teams that want a reusable workflow, not just one-off prompting
  • Product ops or design review teams that need a consistent delivery gate
  • Teams using Feishu/Lark as the place where review feedback actually gets resolved

Three Core Workflows

1. Generate a draft with create-prd-skill

Start from a business brief, workshop notes, or even a one-line idea. The generator classifies the request by complexity, chooses the right chapter depth, and produces a structured PRD scaffold instead of a generic wall of text.

Best for:

  • New feature PRDs
  • Internal system specs
  • Module-level solution drafts
  • Turning meetings into first-pass product docs

2. Review with check-prd-skill

Review a PRD using the right path for the document you actually have:

  • Path A for standard, chapter-based PRDs
  • Path B for messy, free-form docs that still need rigorous review

This keeps review quality high even when documentation quality is uneven.

Best for:

  • Pre-dev readiness review
  • Cross-functional PRD critique
  • System design quality checks
  • Catching missing flows, data, permissions, and exception handling

3. Close the loop in feishu-prd-review-loop

Push findings back into Feishu/Lark, collect 采纳 / 不采纳, generate confirmation cards before any document edit, log waivers, and decide whether the PRD is truly ready for development.

Best for:

  • PRD review in Feishu docs
  • PM/design/dev alignment workflows
  • Auditability for review decisions
  • Teams that want a real delivery gate, not just comments scattered across threads

Architecture

PRD Writing Toolkit workflow

The production prompt, structured diagram data, and exported assets for this workflow live in assets/diagrams/.

Why This Design Is Different

  • Complexity-aware by default: L1-L4 classification prevents over-writing tiny changes and under-specifying large systems.
  • Chapter-first, not checklist-only: when a PRD has structure, review follows that structure. When it does not, the fallback 14-dimension path keeps quality from collapsing.
  • Delivery-gate oriented: the Feishu assistant does not stop at “leave comments”; it tracks replies, confirmations, waivers, and readiness.
  • Progressive loading: skills load only the framework files needed for the current stage, which keeps large workflows more stable in practice.
  • Built for B2B product work: this toolkit assumes business flows, permissions, exceptions, architecture, and rollout matter.

Quick Start

1. Clone the repo

git clone https://github.com/Scofy0123/prd-writing-toolkit.git
cd prd-writing-toolkit

2. Optionally install the canonical shared framework

The bundled skills in this repo already include vendored framework snapshots for zero-dependency installation. If you also want the framework available as a standalone reference module in your local skill inventory, install the top-level prd-quality-framework too:

cp -R prd-quality-framework ~/.claude/skills/prd-quality-framework

3. Install draft generation and review

bash create-prd-skill/install.sh
bash check-prd-skill/install.sh

4. Optionally install the Feishu assistant

This workflow requires lark-cli plus user-authenticated access to the target Feishu/Lark documents.

cp -R feishu-prd-review-loop ~/.agents/skills/feishu-prd-review-loop

5. Start using the workflow

Examples:

  • /create-prd with a business brief to generate the first draft
  • /check-prd with a PRD to run a readiness review
  • Share a feishu.cn doc link and ask for a review loop when you want anchored comments and a delivery decision

Feishu / Lark Collaboration Loop

The Feishu assistant is intentionally more opinionated than a normal commenting bot:

  1. It classifies the PRD scope with L1-L4 complexity
  2. It chooses the actual review chapter set
  3. It writes one issue per anchored comment
  4. It reads reply threads and normalizes 采纳 / 不采纳
  5. It requires PM confirmation before editing the PRD
  6. It logs replies, waivers, and final processing into a feedback base
  7. It evaluates a delivery gate instead of assuming “comments resolved = ready”

That makes it useful for real team workflows where review history matters.

Repository Layout

Module Purpose Upstream Origin
create-prd-skill/ Complexity-aware AI PRD generation Based on pmYangKun/create-prd-skill
check-prd-skill/ Chapter-based review with fallback dimensions Based on pmYangKun/check-prd-skill
feishu-prd-review-loop/ Feishu/Lark review-to-delivery workflow Workflow variant aligned with the check-prd-skill Feishu collaboration branch
prd-quality-framework/ Shared L1-L4 framework, chapter standards, and global checks Packaged here as the first-class foundation of the toolkit

Roadmap

  • Improve standalone installers for one-command setup
  • Add more eval cases for L1/L2 lightweight requirements
  • Expand English-language examples for global discoverability
  • Add more operational templates for review governance and handoff quality

Contributing

  • Improve chapter standards inside prd-quality-framework/
  • Add richer example prompts and PRD samples
  • Contribute Feishu/Lark workflow fixtures and safer integration tests
  • Open issues for gaps in AI PRD generation, PRD review, or delivery gate behavior

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