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project-audit

Audit a project's AI configuration against current project needs and ai-setup to detect duplication, drift, stale instructions, and missing reusable configuration.

来源信息

仓库
ehuerta6/cappy-code
最近来源活动
2026年10月9日 16:11
检测到的 SKILL.md 语言
英语
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安装方式

默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。

检查来源文件

决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。

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SKILL.md
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name
project-audit
description
Audit a project's AI configuration against current project needs and ai-setup to detect duplication, drift, stale instructions, and missing reusable configuration.
# Project audit Audit an existing project's AI configuration. ## Inspect Read: - project instructions and AGENTS files; - current skills, agents, rules, and templates; - product and architecture sources; - Git workflow; - the canonical `ai-setup/README.md` and `ai-setup/WORKFLOWS.md` from the latest available source. If `ai-setup` is not checked out locally, use the canonical repository source supplied by the project or task through an available GitHub connection. If neither source is available, report that comparison gap rather than assuming local copies are current. ## Classify For each relevant configuration item return: - KEEP — correct and project-specific; - UPDATE — still useful but stale or weaker; - REMOVE — unnecessary or duplicated; - MOVE — reusable behavior that belongs in ai-setup; - ADD — useful configuration currently missing. ## Check for - duplicated instructions; - conflicting sources of truth; - stale project decisions; - copied skills that drifted from canonical versions; - oversized instruction files; - configuration with no evidence of use; - recurring friction or successful outcomes recorded in retros or task history; - generic rules embedded in project-specific context. Treat missing usage evidence as unknown, not proof that configuration is unused. Do not change registry adoption status without explicit user approval. Project-specific behavior wins over reusable defaults. Do not make changes until the proposed cleanup is approved. ## Completion Return: - findings; - recommended changes; - affected files; - migration risks.
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