What makes Qcsd Quality Gates notable?

1.1K downloads. Trust evidence available

How should Qcsd Quality Gates be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Qcsd Quality Gates

AI辅助个人开发者代码质量门禁，覆盖需求到交付全流程，自动检查与修复依赖、语法、路径和启动问题。 Skill: Qcsd Quality Gates Owner: ai-acheng Summary: AI辅助个人开发者代码质量门禁，覆盖需求到交付全流程，自动检查与修复依赖、语法、路径和启动问题。 Tags: latest:1.1.1 Version history: v1.1.1 | 2026-08-17T08:56:44.618Z | auto - Added LICENSE, __tests__, and src directories for improved structure and testing. - Removed redundant file skill-card.md. - No changes to SKILL.md content or core quality gate features. - Initializes formal licensing and testing support in

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.1k

Updated

Oct 11, 2026

Version

1.1.1

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1.1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.1.1release · observed Aug 17, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17e1hdx8tza0g6m8aaym7p9ex84vv0m:qcsd-quality-gates

Node.js workspace detected. Install dependencies securely: run `npm ci --ignore-scripts` to prevent post-install lifecycle triggers from running arbitrary code, then selectively audit the dependency tree.
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-ai-acheng-qcsd-quality-gates/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

25,506 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

# QCSD Development 质量门禁技能

## 描述

AI辅助代码开发质量门禁与自动修复，适合个人开发者，保证代码质量，减少低级错误，结合腾讯全AI自动化研发实践改进。

## 功能

- ✅ 完整的6步质量门禁检查流程
- ✅ 自动治理常见开发问题（依赖错误/路径错误/语法错误/启动失败）
- ✅ 标准化项目文件结构（Next.js）
- ✅ 遵循 Conventional Commits 提交规范
- ✅ 适配个人开发者多项目并行开发场景

## 触发条件

- 每次开发新项目，必须执行质量门禁检查
- 每次输出代码给用户，必须过一遍门禁，自动修复问题再交付
- 用户要求检查质量，立即强制执行

## 质量门禁检查清单

### 1. 需求阶段
- 需求完整清晰，所有核心需求点都已记录
- 模糊歧义点已经澄清
- 需求范围符合「单人可开发」
- **识别核心高风险点**：确认哪些功能出问题会影响核心流程，要求必须有对应测试覆盖

### 2. 架构设计阶段
- 技术选型适合个人开发，依赖最小化
- 文件结构符合标准化
- 数据库设计合理，索引正确

### 3. 编码阶段
- TypeScript语法正确
- 所有import路径正确
- 变量函数命名清晰
- 没有冗余代码，注释够用
- 所有需求点都已实现

### 3.5 AI生成代码专项检查（如代码由AI生成，必检）
> 参考经验：AI生成代码容易"看起来能跑，实际埋坑"，这5关必须过
- [ ] **覆盖面有效性**：代码/测试保护的是核心高风险点吗？失败了会不会真影响业务？如果答不上来，重构
- [ ] **语义化稳定性**：定位器/步骤描述绑定业务语义，不靠`nth-child`、长CSS路径、位置猜测
- [ ] **断言业务对齐**：先验证业务状态（数据/接口/数据库），再验证UI提示，不只做"截图打卡"
- [ ] **隐式依赖清理**：不存在无理由固定时间等待，所有前置依赖显式说明
- [ ] **失败可观测性**：测试失败后有足够日志/证据能快速定位问题

### 4. 依赖检查
- `package.json` 包含所有需要的依赖
- 没有多余依赖
- 版本选择稳定

### 5. 环境配置
- `.env.example` 包含所有需要的环境变量
- 每个配置项有说明注释

### 6. 交付前整体检查
- 所有需求点都已实现
- `README.md` 完整（介绍+配置+启动命令）
- 数据库初始化SQL完整
- `.gitignore` 正确
- **可调试性检查**：测试用例失败后能通过日志/截图快速定位问题，大段用例已拆分

## 自动修复能力

- **依赖安装报错** → 自动分析错误，修改版本或移除冲突依赖
- **import路径错误** → 自动查找正确路径修复
- **语法错误** → 自动修正语法和类型错误
- **启动失败** → 自动读取错误日志，定位问题修复
- **缺失文件** → 自动创建
- **AI代码坏味道自动治理**：
  - 扫描硬编码`nth-child`/长CSS定位器，提示替换为语义化写法（`getByRole`/`getByTestId`/`getByLabel`）
  - 发现无理由`waitForTimeout()`添加TODO注释，提示替换为状态断言等待
  - 检测到只有UI可见性断言，提示补充业务状态断言
  - 识别重复冗余定位，建议合并重构

## 作者

pejic

## 许可证

MIT

README.md

# AI-assisted Code Development Quality Gates & Auto-healing

质量门禁&自动修复，适合AI辅助个人开发，保证代码质量，减少低级错误。

## 📋 功能

- ✅ 完整的6步质量门禁检查
- ✅ 自动治理常见问题（依赖错误/路径错误/语法错误/启动失败）
- ✅ 标准化文件结构（Next.js项目）
- ✅ 遵循 Conventional Commits 国际提交规范
- ✅ 结合腾讯全AI自动化研发实践，适配个人开发者多项目并行开发

## 触发条件

- 每次开发新项目，必须执行质量门禁检查
- 每次输出代码给用户，必须过一遍门禁，自动修复问题再交付
- 用户要求检查质量，立即强制执行

## 质量门禁

### 1. 需求阶段
- 需求完整清晰，所有核心需求点都已记录
- 模糊歧义点已经澄清
- 需求范围符合「单人可开发」
- **识别核心高风险点**：确认哪些功能出问题会影响核心流程，要求必须有对应测试覆盖

### 2. 架构设计阶段
- 技术选型适合个人开发，依赖最小化
- 文件结构符合标准化
- 数据库设计合理，索引正确

### 3. 编码阶段
- TypeScript语法正确
- 所有import路径正确
- 变量函数命名清晰
- 没有冗余代码，注释够用
- 所有需求点都已实现

### 3.5 AI生成代码专项检查（必检）
> AI生成代码容易"看起来能跑，实际埋坑"，这5关必须过：
> 1. **覆盖面**：保护的真的是核心风险点吗？失败了会不会拦版本？
> 2. **稳定性**：定位器/描述绑定业务语义，不靠位置猜测
> 3. **断言对齐**：先验证业务状态，再验证UI提示
> 4. **依赖透明**：没有无理由固定等待，所有依赖显式说明
> 5. **可调试**：失败后能快速定位问题

### 4. 依赖检查
- `package.json` 包含所有需要的依赖
- 没有多余依赖
- 版本选择稳定

### 5. 环境配置
- `.env.example` 包含所有需要的环境变量
- 每个配置项有说明注释

### 6. 交付前整体检查
- 所有需求点都已实现
- `README.md` 完整（介绍+配置+启动命令）
- 数据库初始化SQL完整
- `.gitignore` 正确
- **可调试性检查**：测试失败后能快速定位问题

## 自动治理

- **依赖安装报错** → 自动分析错误，修改版本或移除冲突依赖
- **import路径错误** → 自动查找正确路径修复
- **语法错误** → 自动修正语法和类型错误
- **启动失败** → 自动读取错误日志，定位问题修复
- **缺失文件** → 自动创建
- **AI代码坏味道自动治理**：
  - 扫描硬编码`nth-child`/长CSS定位器，提示替换为语义化写法
  - 发现无理由固定等待，提示替换为状态断言
  - 提醒补充缺失的业务状态断言
  - 识别重复冗余代码建议重构

## 标准化文件结构 (Next.js)

```
project-name/
├── app/
│   ├── page.tsx
│   ├── layout.tsx
│   ├── globals.css
│   └── types.ts
├── lib/
│   ├── supabase.ts
│   ├── openai.ts
│   └── *.ts
├── public/
├── data/
├── .env.example
├── .gitignore
├── package.json
├── tsconfig.json
├── next.config.js
├── tailwind.config.ts
├── postcss.config.js
├── README.md
└── *-init.sql
```

## 代码质量标准

- TypeScript：正确类型，不滥用any
- 命名：清晰见名知意
- 注释：复杂逻辑有注释
- 样式：优先Tailwind CSS，不写冗余CSS
- 冗余：删除没用的代码

## AI生成代码Review Checklist

快速人工复核，5问即可：

```
- [ ] 这条代码/测试失败时，我会真的拦版本吗？
- [ ] 定位/描述是不是绑在业务语义上？
- [ ] 断言有没有先看业务结果，再看页面提示？
- [ ] 有没有无理由的固定等待/隐式依赖？
- [ ] 出问题后能不能快速找到根因？
```

## 作者

pejic

## 许可证

MIT

_meta.json

{
  "ownerId": "kn7ffzw77tj6c8yw14p92w963984vgsq",
  "slug": "qcsd-quality-gates",
  "version": "1.1.1",
  "publishedAt": 1786957004618
}

skill-card.md

## Description:

Provides AI-assisted code quality gate guidance for personal development workflows, covering requirements, architecture, coding, dependencies, environment setup, and delivery checks.

This skill is ready for commercial/non-commercial use.

## Publisher:

[ai-acheng](https://clawhub.ai/user/ai-acheng)

### License/Terms of Use:

MIT

## Use Case:

Developers and solo builders use this skill to apply a repeatable quality-gate checklist to AI-assisted code work and to identify issues before handoff or release.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Security evidence says the skill may overstate automatic checking and repair behavior while its runtime can report success without inspecting the project.

Mitigation: Treat pass results as advisory and require human review or independent test evidence before relying on the gate for release decisions.

Risk: The skill describes automatic dependency, path, syntax, startup, and missing-file repairs that may modify a project.

Mitigation: Review proposed dependency changes and file modifications before accepting them, especially in production or customer-facing projects.

## Reference(s):

- [Server-resolved source repository](https://github.com/AI-aCheng/qcsd-quality-gates)
- [ClawHub skill listing](https://clawhub.ai/ai-acheng/skills/qcsd-quality-gates)

## Skill Output:

**Output Type(s):** [guidance, markdown, code, shell commands, configuration]

**Output Format:** [Markdown guidance and checklist-style recommendations, with structured pass/fail status when invoked as a runtime skill.]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Inputs include a project path and an optional AI-generated-code flag.]

## Skill Version(s):

1.1.1 (source: server release metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

package.json

{
  "name": "qcsd-quality-gates",
  "version": "1.0.0",
  "description": "Quality gates and auto-healing for AI-assisted personal development",
  "main": "src/index.ts",
  "scripts": {
    "test": "jest"
  },
  "keywords": [
    "openclaw",
    "skill",
    "quality",
    "codegen",
    "qcsd"
  ],
  "author": "pejic",
  "license": "MIT",
  "devDependencies": {
    "jest": "^29.7.0"
  }
}

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