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Req Change Workflow

Community
yunshu0909
req-change-workflow

已有功能的需求变更闭环(门禁式七步)。触发硬条件:要改的功能已经实现并跑起来了。当用户说"改需求""需求变更""调整交互""改功能""重构流程",或改动容易散到多个文件、碰到鉴权/存储/配置/权限、需要可靠验证 + 回滚方案时使用。流程:锁 scope 写 change brief → 从代码确认当前行为(不靠记忆和假设)→ 影响面与风险评估 + 回滚计划 → 提出新设计等用户批准(**未获批准绝不动代码**)→ 小而局部的 diff → 跑固定回归清单 → 更新文档和决策日志。产出:change brief + 代码 diff + 回归记录 + decision log。不适用于:全新功能从零做(走 issue-pool → page-solution-design(有界面时)→ backend-logic-design(有规则需讨论时)→ prd-test-writer)、只改视觉样式不动任何逻辑(按已有界面直接调整)、新想法还没定要不要做(先用 issue-pool 入池)、写 PRD/测试用例(用 prd-test-writer)、提交推送发版(用 git-push)。注意:本 skill 的七步流程通用于任何项目,但 scripts/impact_scan.sh 与 references/chrome-extension-regression-example.md 是 Chrome 扩展示例;通用回归使用 references/regression-checklist.md,按项目实际选择检查。

Overview

Publisheryunshu0909
Repositoryyunshu_skillshub
Skill namereq-change-workflow
Stars
769
Forks
109
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by yunshu0909 on GitHub. Read the source before you install it.

Installation

Install the Req Change Workflow AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/yunshu0909/yunshu_skillshub/tree/master/coding/req-change-workflow
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yunshu0909/yunshu_skillshub.git /tmp/yunshu_skillshub
mkdir -p .claude/skills
cp -r /tmp/yunshu_skillshub/coding/req-change-workflow .claude/skills/req-change-workflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Req Change Workflow in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Req Change Workflow on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Req Change Workflow is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Req Change Workflow

Overview

Use a lightweight, repeatable workflow to modify an existing requirement without scope creep or “边改边炸”. Produce clear artifacts at each gate so the user can approve before the implementation starts.

Workflow (gated loop)

Follow the steps in order. Do not implement code changes until the user approves Step 4.

Step 0: Set the plan (optional but recommended)

  • Use update_plan to create 5–7 short steps: clarify → baseline → impact → design → implement → validate → document.
  • Keep exactly one step in_progress at a time and advance as you finish.

Step 1: Clarify the change (lock scope first)

Ask the user for the minimal inputs, then rewrite them into a clear “change brief”:

  • Target (1 sentence): what outcome changes.
  • Out of scope (1 sentence): explicitly what must NOT change.
  • Acceptance criteria (3–6 bullets): observable behaviors that can be verified.
  • “Must keep” constraints: compatibility, performance, security, no new dependencies, no network, etc.
  • Rollback expectation: can we revert by reverting a diff, or does it require data migration/backfill?

Use the template in references/change-brief-template.md.

Step 2: Confirm current behavior from code (baseline)

Do not trust memory or assumptions. Locate the real entrypoints + current data flow and summarize it in 5–10 lines:

  • UI entrypoints (e.g., sidepanel/, options/) and where user actions are wired.
  • Background orchestration (e.g., service_worker.js).
  • Core modules (e.g., src/core/...) and storage (src/core/local/...).
  • Config/permissions changes (e.g., manifest.json).

For Chrome extension projects, scripts/impact_scan.sh can help locate likely files. For other projects, use their actual entrypoints and search tools. Then read the relevant implementation to confirm behavior.

Output artifact: “Current behavior summary” + a short file list (with why each file matters).

Step 3: Impact + risk assessment (change budget)

Before proposing a new design, list:

  • Files/modules that must change and why.
  • Risks: auth/session, storage migration, concurrency, caching, permission scopes, UX regressions.
  • Testing checkpoints: what to verify manually (use references/regression-checklist.md).
  • Rollback plan: what is safe to revert; what needs cleanup.

If changes touch manifest.json or service_worker.js, require a manual reload step in the validation plan (Chrome extensions cache aggressively).

Output artifact: “Impact & risk list” + “Rollback plan (1–3 bullets)”.

Step 4: Propose the new design (get approval)

Describe the new behavior using:

  • New flow (bullet sequence) including edge cases.
  • State model: key states, transitions, and failure recovery.
  • Change boundaries: what stays unchanged.
  • Observability: logs/events/UI hints for debugging.

Then ask the user to approve:

  • The acceptance criteria (Step 1) as final.
  • The file list (Step 2/3) as the change budget.
  • The proposed design (this step).

Do not start editing code until the user says “同意/OK/按这个做”.

Step 5: Implement with minimal, localized diffs

Implementation rules:

  • Prefer root-cause fixes over patches, but keep diffs small and focused.
  • Avoid scattering logic across multiple entrypoints; centralize in one module when possible.
  • Keep ES module imports explicit; avoid implicit globals.
  • Add short JSDoc for exported functions when introducing new exports.
  • User-visible logs: actionable Chinese messages (explain what to do next).

If the change involves async flows/cross-module calls/fallbacks, add Chinese comments explaining assumptions and failure handling.

Step 6: Validate (fixed regression loop)

  • Select automated and manual checks from references/regression-checklist.md based on the actual project and change. Record the commands and observed results. Chrome extension examples are in references/chrome-extension-regression-example.md.
  • If manifest.json or service_worker.js changed: reload the extension before retesting.
  • Record what you tested and the observed outcome (even if it is manual).

Step 7: Maintain (docs + decision log)

  • Update project docs or inline notes for future maintainers.
  • Add a short “Decision log” entry: why this design, what alternatives were rejected, and how to roll back.

Use the template in references/decision-log-template.md.

Resources

scripts/

  • scripts/impact_scan.sh: fast file candidate scan via rg for keywords + common extension entrypoints.

references/

  • references/change-brief-template.md: input template to lock scope + acceptance criteria.
  • references/regression-checklist.md: project-neutral regression checklist.
  • references/chrome-extension-regression-example.md: optional Chrome extension example.
  • references/decision-log-template.md: lightweight decision record template.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Req Change Workflow AI skill do?

已有功能的需求变更闭环(门禁式七步)。触发硬条件:要改的功能已经实现并跑起来了。当用户说"改需求""需求变更""调整交互""改功能""重构流程",或改动容易散到多个文件、碰到鉴权/存储/配置/权限、需要可靠验证 + 回滚方案时使用。流程:锁 scope 写 change brief → 从代码确认当前行为(不靠记忆和假设)→ 影响面与风险评估 + 回滚计划 → 提出新设计等用户批准(**未获批准绝不动代码**)→ 小而局部的 diff → 跑固定回归清单 → 更新文档和决策日志。产出:change brief + 代码 diff + 回归记录 + decision log。不适用于:全新功能从零做(走 issue-pool → page-solution-design(有界面时)→ backend-logic-design(有规则需讨论时)→ prd-test-writer)、只改视觉样式不动任何逻辑(按已有界面直接调整)、新想法还没定要不要做(先用 issue-pool 入池)、写 PRD/测试用例(用 prd-test-writer)、提交推送发版(用 git-push)。注意:本 skill 的七步流程通用于任何项目,但 scripts/impact_scan.sh 与 references/chrome-extension-regression-example.md...

Why use Req Change Workflow on TypingMind?

Because you install it once and use it with any model. Req Change Workflow is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Req Change Workflow in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yunshu0909/yunshu_skillshub/tree/master/coding/req-change-workflow. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Req Change Workflow?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Req Change Workflow?

As many as you like. As long as a model supports skills, you can use Req Change Workflow with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Req Change Workflow AI skill free?

Yes. It is published on GitHub by yunshu0909 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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