E
eslamnegm010/ai-dev-workflow
Claude Code skill: plan → implementer agent → quality gate → reviewer agent → merge, with golden tests…
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
安装与配置
客户端配置(取自该仓库的安装命令)
{
"mcpServers": {
"eslamnegm010-ai-dev-workflow": {
"command": "npx",
"args": ["playwright"]
}
}
}解析自我们于 2026-11-11 抓取的该仓库 README;我们未执行过。
command/args 来自仓库写明的安装命令;不确定时请以该项目 README 为准。
VS Code(.vscode/mcp.json —— 键名是 servers)
{
"servers": {
"eslamnegm010-ai-dev-workflow": {
"command": "npx",
"args": ["playwright"]
}
}
}VS Code 顶层键是 <code>servers</code>,其余与上面那份相同。
Claude Code(命令行)
claude mcp add --transport stdio eslamnegm010-ai-dev-workflow -- npx playwright
Claude Code 不收 JSON 文件,用这条命令直接加。
配置项的键名以你的客户端为准:客户端与 CLI
- ★ 数取值
- 0 ★ · eslamnegm010/ai-dev-workflow · 取自 GitHub 搜索 API · (2026-11-13 20:00:50 核对)
- 来源明细
- 从该仓库的 GitHub 页面直接读取 · 条目类型:开源项目
- 收录与活跃
- 收录于 2026-11-12 · 最近见到 2026-11-14 · 共见到 3 次 · 被 1 个来源列出
- 评分构成
- 综合分 103 · 1 个来源 · repo
- 安装
npx playwright
常见问题(答案都来自我们的记录)
怎么安装?
该仓库给出的安装命令是
npx playwright。我们的记录里它是仓库自己提供的;不保证在你的客户端上直接可用。它适合谁 / 用来做什么?
我们把它归在这些标签下: 开源项目。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库
eslamnegm010/ai-dev-workflow;我们收录于 2026-11-12;最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。A Claude Code skill that makes AI agents ship code the way a careful senior team
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
separate agent writes the code, a hard quality gate checks the whole repo, and a third agent, which never saw the
plan, reviews the pushed PR. Screens are checked pixel by pixel against the design with golden tests. Every step
is written down in the repo, so any new session can pick up exactly where the last one stopped.
sh
curl -fsSL https://raw.githubusercontent.com/eslamnegm010/ai-dev-workflow/main/install.sh | bash
Then open Claude Code in any repository and say "set up the AI dev workflow here".
Contents: Why · The loop · Roles · Quality gate ·
Golden tests · Reviews · Status files ·
Examples · Install · Use it · Optional modules
## Why
AI agents write a lot of code quickly. Without a process they also guess at missing specs, approve their own work,
"fix" failing tests by weakening them, drift from the design, and forget everything when the context is compacted.
| Problem | What the workflow does about it |
| The agent invents behaviour, copy or pixels | Translate, don't invent. Every gap is logged as a discrepancy with options and a recommendation. The owner decides product questions; small technical gaps are decided and marked "delegated" |
| The same agent writes and approves the code | Three separate roles: the planner, the implementer (a new instance for every task) and the reviewer (one per PR, reading only the pushed diff) |
| "All tests pass" when they don't | The main session re-runs the gate itself. The gate covers the whole repo before every push, PR and merge |
| Tests edited until they go green | Never edit a test just to make it pass. Key tests are mutation-checked: break the code, watch the test fail, restore |
| The UI drifts from the design | Golden tests against captured design references, in every theme and language, with diff images and similarity scores |
| A new session doesn't know where things stand | Living status files: a progress log, a RESUME HERE line and every standing rule, in the repo |
| Endless fix rounds | Take over after the second failed round. Another round means the hand-off failed |
## The loop
Every substantive task runs these six steps. Small or mechanical tasks (docs, copy, config, renames) skip the agents:
the main session makes the change, runs the gate and self-reviews against the Definition of Done. The process
scales with the task.
Around the loop, the skill ships the whole method: stages with exit gates (alignment → foundation → design system
→ feature loop → hardening → release), a precedence table for sources of truth, Definition of Ready and Done, PR
sizing (≤ ~800 lines, stacked slices), a pre-push checklist, and change management for a new design export, rule
changes, copy and architecture.
## Roles you choose once
The skill asks once per repo, then writes the answer in two places: a dated Roles table in CLAUDE.md, and the
model: line of each agent file. Every later session follows it. A change of mind adds a new dated row, so the
history stays visible.
implementer: a fresh instance for every task. It builds exactly the plan, writes the tests, mutation-checks
the ★ tests, passes the gate and commits locally. It never pushes.
reviewer: one instance per PR, reused for that PR's rounds and replaced for the next PR, so it carries no
plan, reviews the pushed PR. Screens are checked pixel by pixel against the design with golden tests. Every step
is written down in the repo, so any new session can pick up exactly where the last one stopped.
sh
curl -fsSL https://raw.githubusercontent.com/eslamnegm010/ai-dev-workflow/main/install.sh | bash
Then open Claude Code in any repository and say "set up the AI dev workflow here".
Contents: Why · The loop · Roles · Quality gate ·
Golden tests · Reviews · Status files ·
Examples · Install · Use it · Optional modules
## Why
AI agents write a lot of code quickly. Without a process they also guess at missing specs, approve their own work,
"fix" failing tests by weakening them, drift from the design, and forget everything when the context is compacted.
| Problem | What the workflow does about it |
| The agent invents behaviour, copy or pixels | Translate, don't invent. Every gap is logged as a discrepancy with options and a recommendation. The owner decides product questions; small technical gaps are decided and marked "delegated" |
| The same agent writes and approves the code | Three separate roles: the planner, the implementer (a new instance for every task) and the reviewer (one per PR, reading only the pushed diff) |
| "All tests pass" when they don't | The main session re-runs the gate itself. The gate covers the whole repo before every push, PR and merge |
| Tests edited until they go green | Never edit a test just to make it pass. Key tests are mutation-checked: break the code, watch the test fail, restore |
| The UI drifts from the design | Golden tests against captured design references, in every theme and language, with diff images and similarity scores |
| A new session doesn't know where things stand | Living status files: a progress log, a RESUME HERE line and every standing rule, in the repo |
| Endless fix rounds | Take over after the second failed round. Another round means the hand-off failed |
## The loop
Every substantive task runs these six steps. Small or mechanical tasks (docs, copy, config, renames) skip the agents:
the main session makes the change, runs the gate and self-reviews against the Definition of Done. The process
scales with the task.
Around the loop, the skill ships the whole method: stages with exit gates (alignment → foundation → design system
→ feature loop → hardening → release), a precedence table for sources of truth, Definition of Ready and Done, PR
sizing (≤ ~800 lines, stacked slices), a pre-push checklist, and change management for a new design export, rule
changes, copy and architecture.
## Roles you choose once
The skill asks once per repo, then writes the answer in two places: a dated Roles table in CLAUDE.md, and the
model: line of each agent file. Every later session follows it. A change of mind adds a new dated row, so the
history stays visible.
implementer: a fresh instance for every task. It builds exactly the plan, writes the tests, mutation-checks
the ★ tests, passes the gate and commits locally. It never pushes.
reviewer: one instance per PR, reused for that PR's rounds and replaced for the next PR, so it carries no
收录徽章(可选)
想把收录标记放进 README 就复制这行,可选,不影响收录。
[](https://anclum.com/zh/s/eslamnegm010-ai-dev-workflow/)
- 来源
- github · https://github.com/eslamnegm010/ai-dev-workflow
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