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aliyun-skill-creator阿里云技能创建器

Agent Skill

aliyun-skill-creator 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 OpenClaw 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,328

周安装

98

GitHub Stars

公开资料未说明

下载量

815
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:aliyun-skill-creator(阿里云技能创建器)
来源仓库:https://github.com/cinience/aliyun-skill-creator
安装命令:
openclaw skills install aliyun-skill-creator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install aliyun-skill-creator

简介

用于 GitHub 仓库管理与协作流程自动化,支持 Issue 跟踪与 PR 处理。

  • 适合在 OpenClaw 中维护技能生态与代码变更审核。
  • 通过 clawhub 安装后,需绑定有效 GitHub Token 并设置仓库白名单。
  • 涉及敏感代码修改时应双人复核,避免引入安全风险。
  • 注意 API 调用频率限制,合理安排批量操作时间窗口。

SKILL.md

name
aliyun-skill-creator
description
Use when creating, migrating, or optimizing skills for this alicloud-skills repository. Use whenever users ask to add a new skill, import an external skill, refactor skill structure, improve trigger descriptions, add smoke tests under tests/**, or benchmark skill quality before merge.
version
1.0.0

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.
  • skills/**/SKILL.md 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

skills/<domain>/<subdomain>/<skill-name>/
├── SKILL.md
├── agents/openai.yaml
├── references/
│   └── sources.md
└── scripts/ (optional)

tests/<domain>/<subdomain>/<skill-name>-test/
└── SKILL.md

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:

python3 tests/common/compile_skill_scripts.py \
  --skill-path skills/<domain>/<subdomain>/<skill-name> \
  --output output/<skill-name>-test/compile-check.json

Refresh skill index when inventory changed:

scripts/update_skill_index.sh

Confirm index presence:

rg -n "<skill-name>" README.md README.zh-CN.md README.zh-TW.md

Optional broader checks:

make test
make build-cli

5) Benchmark loop (optional, for major skills)

If the user asks for quantitative skill evaluation, reuse bundled tooling:

  • scripts/run_eval.py
  • scripts/aggregate_benchmark.py
  • eval-viewer/generate_review.py

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

  • references/schemas.md
  • references/sources.md

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

75.57%
按下载量换算616

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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