AI Dev Workflow
v1.0.0此技能提供一个标准化、可复现的AI辅助编程工作流，通过三个有序步骤将模糊想法转化为生产就绪的代码：需求转复杂功能描述、描述加技术栈转方法调用结构、结构转完整项目代码。当用户想要开发完整软件系统、从零构建应用程序，或遵循规范的AI-人协作编程流程时，应使用此技能。
⭐ 0· 72·0 current·0 all-time
by波动几何@wangjiaocheng
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description (standardized AI-assisted dev workflow) match the contents: SKILL.md and three detailed reference docs describe samples, prompts, and a three-step pipeline that produce designs and code. There are no unrelated env vars, binaries, or install steps requested.
Instruction Scope
All runtime behavior is described in SKILL.md (read bundled references, apply two built-in prompts, produce structured outputs). This stays within the declared purpose. Note: the skill includes built-in prompts that lock a default architecture/tech-stack (Android, SpringBoot, MySQL, Kotlin); this is coherent but may be surprising if you expected multi-stack flexibility — outputs will follow those defaults unless user overrides them.
Install Mechanism
Instruction-only skill with no install spec and no code files to execute. No downloads, package installs, or archive extraction are present.
Credentials
The skill requests no environment variables, credentials, or config paths. Bundled reference files are local to the skill and used as context; no unrelated secrets are requested.
Persistence & Privilege
Flags show no 'always: true' and default autonomous invocation is allowed (normal). The skill does not request persistent system changes or access to other skills' configs.
Assessment
This skill is instruction-only and internally consistent with its stated purpose, and it does not request credentials or install software — that reduces installation risk. Before using it: (1) be aware the skill embeds two built-in prompts that default to a specific tech stack (Android / SpringBoot / MySQL / Kotlin); if you need a different stack, explicitly override those variables when running the workflow; (2) treat generated code as a scaffold — review, test, and security-audit any production code the skill generates (it can contain bugs, insecure defaults, or license issues); (3) avoid feeding sensitive credentials or private repository secrets into the workflow or prompts (the skill itself does not request them, but downstream use could); and (4) note the skill's provenance is unknown (no homepage/author verification) — rely on code review and testing rather than implicit trust in the provider.Like a lobster shell, security has layers — review code before you run it.
latestvk9773ew0y0dj5cdgvcfqpt0rn584gp79
License
MIT-0
Free to use, modify, and redistribute. No attribution required.