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Aliyun Skill Creator

Name: Aliyun Skill Creator
Author: cinience

作者 cinience · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ⚠ suspicious

总下载

当前安装

版本数

在 OpenClaw 中安装

/install aliyun-skill-creator

功能描述

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,...

使用说明 (SKILL.md)

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/\x3Cdomain>/\x3Csubdomain>/\x3Cskill-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/\x3Cdomain>/\x3Csubdomain>/\x3Cskill-name>-test/SKILL.md.
Generated evidence goes to output/\x3Cskill-or-test-skill>/ only.
If skill inventory changes, refresh README index with scripts/update_skill_index.sh.

Standard deliverable layout

skills/\x3Cdomain>/\x3Csubdomain>/\x3Cskill-name>/
├── SKILL.md
├── agents/openai.yaml
├── references/
│   └── sources.md
└── scripts/ (optional)

tests/\x3Cdomain>/\x3Csubdomain>/\x3Cskill-name>-test/
└── SKILL.md

Workflow

Capture intent

Confirm domain/subdomain and target skill name.
Confirm whether this is new creation, migration, or refactor.
Confirm expected outputs and success criteria.

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/).

Add smoke test

Create or update tests/**/\x3Cskill-name>-test/SKILL.md.
Keep it minimal, reproducible, and low-risk.
Include exact pass criteria and evidence location.

Validate locally

Run script compile validation for the skill:

python3 tests/common/compile_skill_scripts.py \
  --skill-path skills/\x3Cdomain>/\x3Csubdomain>/\x3Cskill-name> \
  --output output/\x3Cskill-name>-test/compile-check.json

Refresh skill index when inventory changed:

scripts/update_skill_index.sh

Confirm index presence:

rg -n "\x3Cskill-name>" README.md README.zh-CN.md README.zh-TW.md

Optional broader checks:

make test
make build-cli

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

安全使用建议

This skill appears to do what it claims: repository scaffolding, validation, benchmarking, and result viewing. Before use: 1) Review any external skill source you plan to copy — do not blindly import untrusted repos or run their scripts without inspection. 2) Run the tooling in an isolated environment (container or VM) to avoid accidental process kills or leaking local files. 3) Be aware that the review server embeds and serves workspace files (including binaries) and writes feedback.json; remove or relocate any secrets before running. 4) If you will run scripts that call system tools (make, lsof, subprocess), inspect them first and prefer a read-only validation pass where possible. Overall the package is internally coherent and proportionate to its purpose, but standard repository hygiene and isolation practices are recommended.

功能分析

Type: OpenClaw Skill Name: aliyun-skill-creator Version: 1.0.0 The bundle provides a comprehensive toolset for creating, benchmarking, and optimizing AI agent skills, specifically for the Alibaba Cloud skills repository. It includes several Python scripts that perform high-risk operations: `run_eval.py` uses `subprocess.Popen` to execute the `claude` CLI for trigger testing; `eval-viewer/generate_review.py` starts a local HTTP server to display results and uses `os.kill` to manage port conflicts; and `improve_description.py` interacts with the Anthropic API to refactor skill metadata. While these capabilities are consistent with the stated purpose of 'Skill Engineering,' the broad use of subprocesses, local networking, and external API calls represents a significant security surface. No evidence of intentional malice or data exfiltration was observed.

能力评估

✓ Purpose & Capability

Name/description (Aliyun Skill Creator for the alicloud-skills repo) aligns with the provided scripts and SKILL.md: scaffolding, validation, smoke-test conventions, benchmarking and reviewer tooling. The included Python scripts (packaging, validation, eval runner, review generator) are coherent with the skill's stated purpose.

ℹ Instruction Scope

SKILL.md instructs repository operations (scaffolding under skills/**, updating README index, adding tests, running local validation and benchmark scripts). It also recommends copying external skill source trees when importing — this is expected for migration tasks but introduces risk: copying and running unreviewed external code (or its test scripts) into your workspace can execute arbitrary code. The review/serve tooling embeds and serves workspace files (including arbitrary outputs) — useful for evaluation but could expose sensitive files if run in a repo with secrets.

✓ Install Mechanism

No install spec or external downloads are declared. All bundled tooling is in-repo Python scripts (no installers or network fetches). This is low-risk from an install mechanism standpoint.

✓ Credentials

The skill declares no required environment variables, credentials, or config paths. Runtime instructions reference local repo paths and tools (python, make) which are appropriate for repository tooling.

✓ Persistence & Privilege

always:false and user-invocable:true (default). The skill does not request permanent platform-wide privileges. It does instruct updating repo files (README index) and writing validation/benchmark artifacts to output/, which is expected and scoped to the repository.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install aliyun-skill-creator
安装完成后，直接呼叫该 Skill 的名称或使用 /aliyun-skill-creator 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

Initial public release of aliyun-skill-creator. - Provides a structured workflow for creating, migrating, or optimizing skills within the `alicloud-skills` repository. - Enforces repository conventions for skill paths, naming, frontmatter, and folder structure. - Includes detailed steps for implementing skill changes, adapting external sources, and adding smoke tests. - Offers validation and benchmarking procedures to ensure skill quality before merging. - Supplies clear definition of done and references for repository standards.

元数据

Slug aliyun-skill-creator

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题