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Import Skills

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royeedai royeedai
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uat ai-os acceptance.yaml

acceptance-gate

阶段验收与 Evidence Pack 守卫。在模块完成、阶段交付、准备上线或用户问"是否完成/能交付了吗"时使用。 它负责检查 Definition of Done、证据完整性和阻塞项，给出通过/阻塞结论，并生成 UAT 脚本供用户手工验证。 --- # 验收门禁 本 Skill 用于防止 AI 在缺少证据时过早宣称“完成”。 ## 使用时机 - 模块开发完成后准备验收 - 阶段交付前需要确认是否具备完成证据 - 用户问“是否完成了”“现在能交付了吗” - `code-review-guard` 需要给出最终通过 / 阻塞结论 ## 使用方式 1. 先识别当前模块的模块类型（`页面类` / `API 类` / `数据处理类` / `工具类`）和交付等级（`L1` / `L2` / `L3`） 2. 读取 `.spec.md`、`.ai-os/tasks.yaml`、`.ai-os/verification-matrix.yaml`、测试结果、构建结果、截图、接口样例或日志 3. 使用模板生成或更新 `.ai-os/acceptance.yaml` 4. 检查每个验收项是否有对应证据 5. 输出通过项、阻塞项、建议优化项 6. 仅在需要人工验证的场景下生成 UAT 脚本；若存在 blocker，不得把结果表述为“已完成” ## 约束 - 没有 Evidence Pack 时，不得用“基本完成”“差不多可交付”替代正式结论 - 只在确实需要人工验证的场景生成 UAT，不要对所有模块机械追加 - 本 Skill 负责验收门禁，不替代代码自审、正式发布检查或事故处理 ## 通用必查项 - Definition of Done 是否满足 - Evidence Pack 是否完整 - 本次变更要求的 restart / cold-start 验证是否已执行并留痕 - blocker 是否被显式记录 - 需求变更是否已同步到 spec / tasks / tests - 准备上线时是否还缺发布或回滚条件 ## 按模块类型检查验收证据 ### 页面类 - 至少存在关键页面截图、录屏或等价界面证据 - 至少存在一条可执行的人工验证路径 - 状态处理、权限和关键交互有可观测结果 ### API 类 - 至少存在请求 / 响应样例、契约测试或等价接口证据 - 错误处理和权限控制有可观测结果 - 如涉及数据写入，需说明幂等 / 回滚 / 风险边界 ### 数据处理类 - 至少存在运行日志、结果样例或等价执行证据 - 输入、输出、失败重试 / 补数策略已验证 - 如涉及调度，需说明触发方式和失败后的恢复路径 ### 工具类 - 至少存在命令执行样例、帮助输出或等价运行证据 - 参数 / 配置 / 输出格式已验证 - 安装 / 运行方式和失败退出行为可复现 ## 按交付等级缩放验收 ### L1 探索 - 允许轻量 Evidence Pack - 最少需要：构建或运行成功证据 + 一个关键结果证据 + 已知限制说明 - 若没有用户可见界面，可不强制生成完整 UAT 脚本 ### L2 标准 - 需要完整的 DoD 检查、构建 / 测试证据、关键结果证据和 UAT 脚本（如适用） - 对用户可见模块，必须有可执行 UAT ### L3 高风险 - L2 全部满足 - 已执行或明确记录 `security-guard`、`architecture-reviewer`、`release-manager` 相关结论 - 已明确发布、回滚、审批点和高风险剩余事项 ## 派生规则检查 - 按 `.agents/references/derived-rules.md` 的“共享基础能力优先”规则，检查阶段验收是否满足“基础能力可用 + 首条核心业务闭环可运行”，而不是只完成孤立模块 ## 模板引用 - 验收清单：读取 `.agents/templates/project/acceptance.yaml` 作为模板生成 `.ai-os/acceptance.yaml` ### 示例：页面类模块验收结论 - 输入：页面类模块 `.spec.md`、任务完成证据、关键页面截图、测试结果 - 输出：更新 `.ai-os/acceptance.yaml`，并明确“通过 / 阻塞 / 建议优化” - 约束：若截图、录屏或关键日志缺失，则结论只能是阻塞或待补证据 ## UAT 脚本模板 验收报告末尾在“需要人工验证”的场景下附带 UAT 脚本，供用户手工验证。 ```markdown ## 人工验证脚本（UAT） ### 前置条件 - [ ] 本地环境已启动（命令：`[启动命令]`） - [ ] 已具备测试数据 / 测试账号 ### 正常路径验证 | # | 操作步骤 | 预期结

⬇0 ❤7 7 days ago · Uploaded Detail →

Skill File Structure Sample (Reference)

skill-sample/
├─ SKILL.md              ⭐ Required: skill entry doc (purpose / usage / examples / deps)
├─ manifest.sample.json  ⭐ Recommended: machine-readable metadata (index / validation / autofill)
├─ LICENSE.sample        ⭐ Recommended: license & scope (open source / restriction / commercial)
├─ scripts/
│  └─ example-run.py     ✅ Runnable example script for quick verification
├─ assets/
│  ├─ example-formatting-guide.md  🧩 Output conventions: layout / structure / style
│  └─ example-template.tex         🧩 Templates: quickly generate standardized output
└─ references/           🧩 Knowledge base: methods / guides / best practices
   ├─ example-ref-structure.md     🧩 Structure reference
   ├─ example-ref-analysis.md      🧩 Analysis reference
   └─ example-ref-visuals.md       🧩 Visual reference

More Agent Skills specs Anthropic docs: https://agentskills.io/home

SKILL.md Requirements

├─ ⭐ Required: YAML Frontmatter (must be at top)
│  ├─ ⭐ name                 : unique skill name, follow naming convention
│  └─ ⭐ description          : include trigger keywords for matching
│
├─ ✅ Optional: Frontmatter extension fields
│  ├─ ✅ license              : license identifier
│  ├─ ✅ compatibility        : runtime constraints when needed
│  ├─ ✅ metadata             : key-value fields (author/version/source_url...)
│  └─ 🧩 allowed-tools        : tool whitelist (experimental)
│
└─ ✅ Recommended: Markdown body (progressive disclosure)
   ├─ ✅ Overview / Purpose
   ├─ ✅ When to use
   ├─ ✅ Step-by-step
   ├─ ✅ Inputs / Outputs
   ├─ ✅ Examples
   ├─ 🧩 Files & References
   ├─ 🧩 Edge cases
   ├─ 🧩 Troubleshooting
   └─ 🧩 Safety notes

Why SkillWink?

Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.

We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.

Keyword Search Version Updates Multi-Metric Ranking Open Standard Discussion

Quick Start:

Import/download skills (.zip/.skill), then place locally:

~/.claude/skills/ (Claude Code)

~/.codex/skills/ (Codex CLI)

One SKILL.md can be reused across tools.

FAQ

Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.

1. What are Agent Skills?

A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.

Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.

2. How do Skills work?

Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.

This keeps agents lightweight while preserving enough context for complex tasks.

3. How can I quickly find the right skill?

Use these three together:

  • Semantic search: describe your goal in natural language.
  • Multi-filtering: category/tag/author/language/license.
  • Sort by downloads/likes/comments/updated to find higher-quality skills.

4. Which import methods are supported?

  • Upload archive: .zip / .skill (recommended)
  • Upload skills folder
  • Import from GitHub repository

Note: file size for all methods should be within 10MB.

5. How to use in Claude / Codex?

Typical paths (may vary by local setup):

  • Claude Code：~/.claude/skills/
  • Codex CLI：~/.codex/skills/

One SKILL.md can usually be reused across tools.

6. Can one skill be shared across tools?

Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.

Example: retrieval + writing + automation scripts as one workflow.

7. Are these skills safe to use?

Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.

8. Why does it not work after import?

Most common reasons:

  • Wrong folder path or nested one level too deep
  • Invalid/incomplete SKILL.md fields or format
  • Dependencies missing (Python/Node/CLI)
  • Tool has not reloaded skills yet

9. Does SkillWink include duplicates/low-quality skills?

We try to avoid that. Use ranking + comments to surface better skills:

  • Duplicate skills: compare differences (speed/stability/focus)
  • Low quality skills: regularly cleaned up