BC ai-engineering-workflow
用AI写代码一时爽，项目越写越乱火葬场？Superpowers方法论5道Gate卡住质量：设计没想清楚不准动手、没写测试不准提交。把「能跑就行」升级成工程级交付，让AI帮你写出可维护的代码。支持全栈项目（Web/移动端/API/数据）、团队协作规范、CI/CD集成指南。从需求到上线的完整工程化流水线，杜绝"AI生成代码没法维护"的通病。 触发词：AI编程工程化、Superpowers方法论、编程工作流、Gate门槛、TDD驱动、AI开发流程、工程化开发、AI代码规范、代码质量保障、AI辅助开发流程、软件工程质量、AI编程最佳实践、工程化AI、AI code workflow、TDD with AI、AI development process、code quality gates、AI工程实践、AI编码规范、工程化工作流、AI项目管理、持续集成AI、AI代码审查、开发流程优化、AI交付质量、superpowers workflow、AI native engineering、代码可维护性、技术债务管理、AI重构工作流、交付标准、工程化交付、AI代码太乱怎么办、怎么管理AI代码、AI编程流程、工程化方法论、AI代码审查标准、开发规范化、AI生成代码质量、代码工程化、开发流程标准化、AI辅助编程规范、软件质量门禁、agentic engineering、vibe coding to engineering、AI coding workflow、engineering discipline AI 排除：纯代码编写(无流程)、项目管理工具配置、非AI辅助开发、纯代码补全
用AI写代码一时爽，项目越写越乱火葬场？Superpowers方法论5道Gate卡住质量：设计没想清楚不准动手、没写测试不准提交。把「能跑就行」升级成工程级交付，让AI帮你写出可维护的代码。支持全栈项目（Web/移动端/API/数据）、团队协作规范、CI/CD集成指南。从需求到上线的完整工程化流水线，杜绝"AI生成代…
As a process C 59/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches
The same skill appears in 1 more place: ClawHub
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 0. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 59/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 60Result and completion. Output format stated, no completion criterion
- 100Tools and files. No external tools needed
- 100Steps. 87 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1585 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +3Description length 692: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 87 items
- +3Output format is stated explicitly
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.