code-cleanup-audit
Audit a repository for architectural decay, AI-generated code smells, stale compatibility paths, dead abstractions, boundary violations, and cleanup candidates without modifying files. Use when the user asks to review code quality, find bad code, inspect AI-generated code, identi
供给资产档案
编程与开发 Agent
代码审查、仓库分析、测试、CI、GitHub、DevOps 与开发工作流 Skill。
场景
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
适配 Agent
Claude Code + Browser agents + CLI
适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。
安装
就绪
npx skills add pqpo/pragma --skill code-cleanup-audit
维护状态
新鲜
距上次推送 2 天
风险
需审查
Dependency or permission surface needs review
GitHub 质量
100
67/100 质量 · 68/100 信任
覆盖标签
审查说明
Dependency or permission surface needs review · Permission surface may require sandboxing
Agent 采用评分卡
一眼查看信任、审计与安装准备度
这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。
质量
有潜力有用的候选项,但采用前应与替代方案比较。
信任
仅限沙盒有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。
审计
需审查对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。
OpenAgentSkill 信任评分 v5
安装前需人工审查
仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。
Stars
100 个 GitHub Stars
仓库活跃度
100 个 Star,8 个 Fork
维护状态
距上次推送 2 天
许可证
NOASSERTION
安装
npx skills add pqpo/pragma --skill code-cleanup-audit
安装安全性
标准软件包或运行时安装路径
权限范围
secrets or environment access, shell or command execution
Agent 结果
暂未有 Agent 结果数据
文档
README/SKILL.md 上下文充分
风险摘要
生产前审查
- The repository license is detected as NOASSERTION, which may be ambiguous for redistribution, but this does not affect the skill's functionality or safety.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 100 stars, 8 forks; issue activity unavailable in current metadata
安装准备度
安装路径可用
- 安装路径可用
- 仓库证据可用
- 已声明许可证
- 暂无 Agent 验证结果证据
Agent 可读元数据
这个 Skill 的机器可读决策数据。
使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。
适用任务
- GitHub automation 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
- Inspect repository metadata
适用 Agent
安装决策
- 命令
- npx skills add pqpo/pragma --skill code-cleanup-audit
- 策略
- 阻止
- 人工审查
- 是
信任与风险
- 信任
- 60/100
- 审计
- 75/100
- 风险级别
- 需审查
结果闭环
- 端点
- /api/agent/outcome
- 事件 ID
- resolve
- 结果
- 5
不适用场景
- 需要厂商支持 SLA 的团队
- production agents without a repository review
- The repository license is detected as NOASSERTION, which may be ambiguous for redistribution, but this does not affect the skill's functionality or safety.
- 高风险权限提示:Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
Agent 安全 v2
27/100 · 避免自动安装
This skill should not be selected by an agent without explicit human security review.
Do not auto-install. Inspect the source, dependencies, and permission surface first.
高
Shell 或命令执行
Skill 元数据引用了终端、CLI、Shell、子进程或命令执行工作流。
中
Browser automation
Skill may drive a browser or interact with web pages.
中
网络访问
Skill 可能访问远程页面、API、仓库或外部服务。
中
文件系统访问
Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。
- 高风险权限提示:Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
安装目标
在你的 Agent 工作流中安装此 Skill
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install pqpo-code-cleanup-auditAgent 解析计划
让 Agent 在安装前验证匹配度。
Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。
打开 JSON
/api/agent/resolve?task=Use%20code-cleanup-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20code-cleanup-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/pqpo-code-cleanup-audit/install
Agent 应检查
- 从 Resolve API 检查任务匹配与替代方案。
- 检查审计评分、信任评分和安全策略警告。
- 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。
复制提示词
Task: Use code-cleanup-audit in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20code-cleanup-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/pqpo-code-cleanup-audit/install
Install command: npx skills add pqpo/pragma --skill code-cleanup-audit
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent 交接
把安装路径交给 Agent,而不是再给一个目录页。
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
安装交接
/api/skills/pqpo-code-cleanup-audit/install
LLM 文本格式
/api/skills/pqpo-code-cleanup-audit/install?format=text
寻找替代方案
/api/skills/search?q=code-cleanup-audit&limit=3
Agent 提示词
Use code-cleanup-audit for this task. Review https://www.openagentskill.com/api/skills/pqpo-code-cleanup-audit/install, then install with: npx skills add pqpo/pragma --skill code-cleanup-auditRegistry 元数据
用于自动选择 Skill 的 Agent 可读档案。
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
Manifest
/api/registry/manifest/pqpo-code-cleanup-audit
LLM 文本
/api/registry/manifest/pqpo-code-cleanup-audit?format=text
安装别名
/api/registry/install/pqpo-code-cleanup-audit
推荐
/api/registry/recommend?task=Use%20code-cleanup-audit%20in%20an%20agent%20workflow&limit=3
适配 Agent
GitHub automation
平台
Claude Code, Browser agents
Agent 决策面板
Fallback candidate for GitHub automation
先用此 Skill 做原型验证,并保留备选方案。
栈中角色
备选候选
主要匹配
GitHub automation
信任标签
先做原型验证
安装路径
命令已就绪
适用场景
- GitHub automation 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
证据
- 仓库近期活跃
- 已提供安装命令或 GitHub 仓库
- 67/100 质量档案
- 4 个 OpenAgentSkill 交互事件
先审查
- The repository license is detected as NOASSERTION, which may be ambiguous for redistribution, but this does not affect the skill's functionality or safety.
实施路径
- 1在沙盒 Agent 中安装它,并端到端完成一次GitHub automation任务。
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
信任档案
仅限沙盒
有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。
GitHub 采用度
信息100 个 GitHub Stars
Star/Fork 活跃度
检查100 个 Star,8 个 Fork; 当前元数据中没有议题活跃度信息
近期维护
通过距上次推送 2 天
许可证清晰度
通过NOASSERTION
积极信号
- AI 审查已通过
- 安装路径可用
- 仓库证据可用
- 近期维护的仓库
- 安装命令未发现明显高风险模式
- 结果闭环已就绪,但需要首次真实 Agent 运行
安装前审查
- The repository license is detected as NOASSERTION, which may be ambiguous for redistribution, but this does not affect the skill's functionality or safety.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 100 stars, 8 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- 暂未有真实 Agent 结果报告
- 无人值守安装前需要人工审查
建议操作
仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。
质量档案
有潜力 适用于 Agent 工作流的候选
有用的候选项,但采用前应与替代方案比较。
工作流匹配
在这些场景使用此 Skill
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Operate web apps
Browser automation
I need my agent to control a browser, fill forms, and verify web app workflows.
工作流匹配
加入完整工作流
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
Wazuh
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Maigret
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概览
--- name: code-cleanup-audit description: Audit a repository for architectural decay, AI-generated code smells, stale compatibility paths, dead abstractions, boundary violations, and cleanup candidates without modifying files. Use when the user asks to review code quality, find bad code, inspect AI-generated code, identify refactoring or cleanup opportunities, detect legacy leftovers, or produce a cleanup backlog that requires human confirmation before implementation. ---
# Code Cleanup Audit
## Overview
Use this skill to produce an evidence-backed cleanup audit only. The output is a backlog of suspected or confirmed problems for human review, not an implementation plan that silently edits code.
## Non-Negotiable Guardrails
- Do not modify files. - Do not call `apply_patch`, formatters with write mode, generators, codemods, install commands, migration commands, or any command whose purpose is to change the workspace. - Do not create branches, commits, pull requests, or issue tickets unless the user explicitly asks after reviewing the audit. - If the user asks for fixes before seeing the audit, first produce findings and ask which items to implement. - If a command unexpectedly changes files, stop, report the changed paths, and ask how to proceed. - Preserve unrelated dirty worktree changes; treat them as user-owned.
## Audit Workflow
1. Establish repository context: - Read `AGENTS.md` first. - Read architecture and convention docs that directly govern the touched codebase, especially dependency boundaries, ADRs, and package conventions. - Run `git status --short` and note existing dirty files. - Inventory apps/packages with read-only commands such as `find`, `rg --files`, `pnpm -r list --depth -1`, and package manifest reads.
2. Build a map before judging: - Identify package boundaries, public exports, app entry points, runtime adapters, shared schemas, tests, and docs. - Trace imports through package names, not only filenames. - Compare implementation structure against documented allowed dependencies. - Prefer `rg` over slower search tools.
3. Inspect for cleanup categories: - Architecture violations: forbidden imports, cross-package relative imports, app-layer logic in shared packages, runtime-specific code in core/shared, browser-unsafe code in web/client/shared. - Stale compatibility: deprecated fields, fallback branches, migration shims, legacy aliases, duplicate old/new APIs, TODOs that preserve obsolete behavior, no-op adapters, unused feature flags. - AI-generated code smells: over-broad abstractions, fake extensibility, duplicated helpers, inconsistent naming, hand-rolled utilities where a project utility exists, speculative layers, uncalled code, verbose comments explaining obvious code, guessed data shapes. - Type and schema weakness: `any`, unsafe casts, unchecked `unknown`, interfaces where runtime validation is required, schema/type drift, missing boundary parsing. - Error and runtime behavior smells: swallowed errors, broad `catch`, impossible states represented as optional fields, missing cancellation/timeout handling, fragile env assumptions. - Test and validation gaps: core behavior without tests, snapshots masking behavior, tests that only assert mocks, missing negative cases for boundary rules. - Documentation drift: docs or AGENTS rules contradicted by code, public API exports not reflected in docs, stale startup/quality commands.
4. Validate suspected issues: - Read surrounding code and tests before reporting. - Run read-only validation where useful: `pnpm lint`, `pnpm typecheck`, `pnpm test`, focused Vitest commands, `pnpm build` only when build behavior is relevant. - Use existing ESLint boundary rules as evidence when available. - Distinguish confirmed problems from cleanup candidates that need product or architectural judgment.
5. Report without fixing: - Lead with findings ordered by severity. - Include file path and line or precise code location for each finding. - State the violated rule or smell, why it matters, evidence, confidence, and suggested cleanup direction. - Mark every item as one of: `confirmed`, `likely`, or `needs human decision`. - Include "Do not modify until confirmed" language when handing off.
## Severity Standard
- `Critical`: Can break runtime behavior, violate security/privacy boundaries, corrupt data, or cause CI/build failure. - `High`: Violates documented architecture, creates wrong package dependency direction, or preserves misleading/dead public API that future agents will copy. - `Medium`: Increases maintenance cost through duplication, stale compatibility, weak validation, or untested shared behavior. - `Low`: Local readability or consistency issue with limited blast radius.
Do not report pure preference, cosmetic style, or speculative rewrites unless tied to a concrete maintenance, correctness, boundary, or future-agent-copying risk.
## Recommended Commands
Use commands like these as applicable. Keep them read-only.
```bash git status --short find apps packages docs -maxdepth 3 -type f | sort rg --line-number "TODO|FIXME|deprecated|legacy|compat|shim|fallback|no-op|noop|any\\b|as unknown|as any" apps packages docs rg --line-number "from ['\"]\\.\\./\\.\\./|from ['\"]\\.\\./\\.\\./\\.\\./|@pragma/(client|server|core|runtime)" apps packages pnpm -r list --depth -1 pnpm lint pnpm typecheck pnpm test ```
Before running expensive repository-wide commands, prefer focused reads and explain why the command is useful.
## Output Format
Return:
1. Findings - Severity - Status: `confirmed`, `likely`, or `needs human decision` - Location - Problem - Evidence - Cleanup direction, without editing code
2. Cleanup backlog - Group related findings into reviewable batches. - Call out which batches are safe mechanical cleanup versus architecture decisions.
3. Non-findings and constraints - Mention important suspected issues that were checked and rejected. - Mention commands run and commands intentionally skipped.
4. Human confirmation needed - List the exact decisions needed before any code changes.
技术详情
- 版本
- 1.0.0
- 许可证
- NOASSERTION
- 最近更新
- 2026年8月20日
- 发布时间
- 2026年8月20日
决策摘要
备选候选
仓库近期活跃
Agent 验证证据
Agent 验证证据
来自解析、审查、安装和一次小范围运行后的结果报告。
- 成功率
- —
- 近期失败
- —
- 结果
- 0
- 输出质量
- —
- 失败
- 0
- 不相关
- 0
- 安装次数
- 0
- 风险拦截
- 0
- 需要配置
- 0
- 生产环境
- 0
暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。
增长闭环
分享工具包
为 code-cleanup-audit 准备的场景化草稿,可手动发布到 X。
A practical pick for source-backed research: code-cleanup-audit: Audit a repository for architectural decay, AI-generated code smells, stale compatibility paths, dead abstractions, boundar... 100 stars https://www.openagentskill.com/skills/pqpo-code-cleanup-audit?ref=x
可选:带安装命令的回复
Listing + install path for code-cleanup-audit: https://www.openagentskill.com/skills/pqpo-code-cleanup-audit?ref=x Install: npx skills add pqpo/pragma --skill code-cleanup-audit
收录来源
Registry 收录
此列表来自公开来源,维护者认领获批前不会标记为官方。
- 创作者
- pqpo
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 Registry 收录 列表归属于 pqpo,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/pqpo-code-cleanup-audit)
[](https://www.openagentskill.com/skills/pqpo-code-cleanup-audit)
[](https://www.openagentskill.com/skills/pqpo-code-cleanup-audit/audit)
[](https://www.openagentskill.com/skills/pqpo-code-cleanup-audit)作者
pqpo
@pqpo
健康信号
- GitHub Stars
- 100
- 质量评分
- 37/100
- 最近 GitHub 推送
- 2026年8月20日
- 框架提示
- 未知
- OpenAgentSkill 浏览量
- 4
- 复制安装命令
- 0
- 跳转点击
- 0
社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
信任与安全
仅限沙盒
- GitHub 采用度100 个 GitHub Stars信息
- Star/Fork 活跃度100 个 Star,8 个 Fork; 当前元数据中没有议题活跃度信息检查
- 近期维护距上次推送 2 天通过
- 许可证清晰度NOASSERTION通过
- README/SKILL.md 完整度元数据包含足够的用法与工作流上下文通过
- 依赖与运行时风险command execution surface, credential or environment access修复
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