Category: tool
Alibaba Cloud Skill Creator
Repository-specific skill engineering workflow for alicloud-skills.
Use this skill when
- - Creating a new skill under
skills/**. - Importing an external skill and adapting it to this repository.
- Updating skill trigger quality (
name and description in frontmatter). - Adding or fixing smoke tests under
tests/**. - Running structured benchmark loops before merge.
Do not use this skill when
- - The user only needs to execute an existing product skill.
- The task is purely application code under
apps/ with no skill changes.
Repository constraints (must enforce)
- - Skills live under
skills/<domain>/<subdomain>/<skill-name>/. - Skill folder names use kebab-case and should start with
alicloud-. - Every skill must include
SKILL.md frontmatter with name and description. - INLINECODE11 content must stay English-only.
- Smoke tests must be in
tests/<domain>/<subdomain>/<skill-name>-test/SKILL.md. - Generated evidence goes to
output/<skill-or-test-skill>/ only. - If skill inventory changes, refresh README index with
scripts/update_skill_index.sh.
Standard deliverable layout
CODEBLOCK0
Workflow
1) Capture intent
- - Confirm domain/subdomain and target skill name.
- Confirm whether this is new creation, migration, or refactor.
- Confirm expected outputs and success criteria.
2) Implement skill changes
- - For new skills: scaffold structure and draft
SKILL.md + agents/openai.yaml. - For migration from external repo: copy full source tree first, then adapt.
- Keep adaptation minimal but explicit:
- Replace environment-specific instructions that do not match this repo.
- Add repository validation and output discipline sections.
- Keep reusable bundled resources (
scripts/,
references/,
assets/).
3) Add smoke test
- - Create or update
tests/**/<skill-name>-test/SKILL.md. - Keep it minimal, reproducible, and low-risk.
- Include exact pass criteria and evidence location.
4) Validate locally
Run script compile validation for the skill:
CODEBLOCK1
Refresh skill index when inventory changed:
CODEBLOCK2
Confirm index presence:
CODEBLOCK3
Optional broader checks:
CODEBLOCK4
5) Benchmark loop (optional, for major skills)
If the user asks for quantitative skill evaluation, reuse bundled tooling:
- - INLINECODE21
- INLINECODE22
- INLINECODE23
Prefer placing benchmark artifacts in a sibling workspace directory and keep per-iteration outputs.
Definition of done
- - Skill path and naming follow repository conventions.
- Frontmatter is complete and trigger description is explicit.
- Test skill exists and has objective pass criteria.
- Validation artifacts are saved under
output/. - README skill index is refreshed if inventory changed.
References
- - INLINECODE25
- INLINECODE26
技能名称:aliyun-skill-creator
详细描述:
类别:工具
阿里云技能创建器
针对 alicloud-skills 仓库的技能工程工作流。
使用此技能的场景
- - 在 skills/ 下创建新技能。
- 导入外部技能并适配到本仓库。
- 更新技能触发质量(frontmatter 中的 name 和 description)。
- 在 tests/ 下添加或修复冒烟测试。
- 在合并前运行结构化基准测试循环。
不使用此技能的场景
- - 用户仅需执行现有产品技能。
- 任务纯粹是 apps/ 下的应用代码,不涉及技能变更。
仓库约束(必须遵守)
- - 技能位于 skills//// 下。
- 技能文件夹名称使用 kebab-case 格式,且应以 alicloud- 开头。
- 每个技能必须包含带有 name 和 description 的 SKILL.md frontmatter。
- skills//SKILL.md 内容必须仅使用英文。
- 冒烟测试必须位于 tests///-test/SKILL.md。
- 生成的证据仅保存到 output//。
- 如果技能清单发生变化,使用 scripts/updateskillindex.sh 刷新 README 索引。
标准交付结构
text
skills////
├── SKILL.md
├── agents/openai.yaml
├── references/
│ └── sources.md
└── scripts/(可选)
tests///-test/
└── SKILL.md
工作流程
1) 捕获意图
- - 确认领域/子领域及目标技能名称。
- 确认是新建、迁移还是重构。
- 确认预期输出和成功标准。
2) 实施技能变更
- - 对于新技能:搭建结构并起草 SKILL.md + agents/openai.yaml。
- 对于从外部仓库迁移:先复制完整源码树,然后进行适配。
- 保持适配最小化但明确:
- 替换与本仓库不匹配的环境特定指令。
- 添加仓库验证和输出规范部分。
- 保留可复用的捆绑资源(scripts/、references/、assets/)。
3) 添加冒烟测试
- - 创建或更新 tests//-test/SKILL.md。
- 保持最小化、可复现且低风险。
- 包含明确的通过标准和证据位置。
4) 本地验证
运行技能脚本编译验证:
bash
python3 tests/common/compileskillscripts.py \
--skill-path skills/// \
--output output/-test/compile-check.json
当清单发生变化时刷新技能索引:
bash
scripts/updateskillindex.sh
确认索引存在:
bash
rg -n README.md README.zh-CN.md README.zh-TW.md
可选更广泛的检查:
bash
make test
make build-cli
5) 基准测试循环(可选,适用于主要技能)
如果用户要求定量技能评估,可复用捆绑工具:
- - scripts/runeval.py
- scripts/aggregatebenchmark.py
- eval-viewer/generate_review.py
建议将基准测试产物放在同级工作目录中,并保留每次迭代的输出。
完成标准
- - 技能路径和命名遵循仓库约定。
- Frontmatter 完整且触发描述明确。
- 测试技能存在且具有客观通过标准。
- 验证产物已保存到 output/ 下。
- 如果清单发生变化,README 技能索引已刷新。
参考资料
- - references/schemas.md
- references/sources.md