aliyun-skill-creatorUse when creating, migrating, or optimizing skills for this alicloud-skills repository. Use whenever users ask to add a new skill, import an external skill,...
Install via ClawdBot CLI:
clawdbot install cinience/aliyun-skill-creatorGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
eval(Calls external URL not in known-safe list
https://github.com/anthropics/skills/tree/main/skills/skill-creatorUses known external API (expected, informational)
googleapis.comAI Analysis
This skill is a repository management tool for scaffolding and validating skill structures, with no functionality that processes or transmits user data. The external references (GitHub, Google APIs) appear to be informational examples or known-safe dependencies, not active data exfiltration channels. The shell commands are for local validation and indexing, not arbitrary execution.
Generated May 6, 2026
When a new cloud service needs an AI skill under the alicloud-skills repository, this skill scaffolds the folder structure, drafts SKILL.md and agents/openai.yaml, and creates a basic smoke test. For example, creating a skill for 'Alibaba Cloud DNS' under skills/network/.
When importing an existing AI skill from an external source (e.g., another repo or a standalone tool), this skill guides copying the source tree and minimally adapting it to match the repository conventions, including frontmatter and validation requirements.
When updating legacy skills to improve trigger descriptions (name, description in frontmatter) or refactor the structure to comply with current standards, this skill provides a systematic workflow to ensure consistency across the repository.
When a skill lacks adequate smoke tests, this skill helps create minimal, reproducible tests under tests/** with objective pass criteria and evidence output, ensuring basic functionality before merge.
When a skill requires quantitative evaluation before merging, this skill runs benchmark loops using bundled scripts (run_eval.py, aggregate_benchmark.py), generating artifacts for review and ensuring the skill meets performance standards.
Provides a structured framework to maintain consistency across AI skill repositories, reducing technical debt and onboarding time for new contributors. Delivers value through enforced conventions and automated validation.
Speeds up creation and migration of AI skills by automating scaffolding, testing, and benchmarking. Enables faster time-to-market for cloud AI capabilities, especially for internal or partner teams.
Integrates smoke tests and benchmark loops into the skill lifecycle, ensuring high-quality releases. This reduces regression risks and improves user trust in deployed skills.
💬 Integration Tip
Ensure the repository is cloned and you have Python and shell access to run validation scripts. Review the references/schemas.md for frontmatter schemas before drafting SKILL.md.
Scored May 6, 2026
Audited Apr 16, 2026 · audit v1.0
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