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Agent Workspace Hygiene

核心功能是针对编码仓库的生成类工件(如缓存、构建输出、临时文件等)进行盘点、清理或归档。典型使用场景为用户明确要求清理工作区、盘点可清理文件、释放磁盘空间时。输入为用户的明确清理请求,输出为简洁的盘点报告与清理计划,默认干运行,需用户确认后执行,优先采用可恢复归档而非永久删除,同时保护受追踪文件、密钥等敏感内容。

hollis9087
hollis9087
热度 16.02
最近更新 2026-05-31 17:43:03
分类:开发依赖:代码执行 / 读写文件应用场景:DevOps / 自动化脚本 / 任务管理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add agent-workspace-hygiene
Metadata
name
workspace-hygiene
description
Use this skill only when the user explicitly asks for a dry-run cleanup inventory, disk-space cleanup, deletion review, or recoverable archiving of generated workspace artifacts in a coding repo, such as caches, logs, test reports, screenshots, temporary databases, eval outputs, build outputs, or agent scratch files. Do not trigger just because the user says a repo is messy, asks for code review, asks for git status, wants README/docs cleaned up, requests memory cleanup, or asks for ordinary coding/testing/refactoring. If cleanup or archive/removal of workspace artifacts is not the main request, do not use this skill.
metadata
{"compatibility":{"os":["windows","macos","linux"],"requires":{"python":"optional","git":"optional"}}}

Workspace Hygiene

Keep this skill quiet, cheap, and user-friendly. It is for cleaning the workspace around the project, not rewriting the project.

Default Flow

  1. Stay silent unless cleanup is explicit. Do not interrupt normal development just because a few files exist. Mention cleanup only when the user directly asks to inventory, remove, or archive workspace artifacts, or asks to reduce disk usage from generated files.

  2. Find the workspace root. Prefer the current repo root. Do not scan the user's home directory or sibling projects unless the user names them.

  3. Take a cheap inventory first. If Python is available, run the read-only helper:

    python <skill-dir>/scripts/workspace_inventory.py --root . --summary-json --max-entries 40 --recent-hours 24
    

    Use python3 if that is the local convention. If Python is unavailable, inspect manually with the same categories below.

  4. If no intervention is needed, say so briefly. Do not produce a long report.

  5. If cleanup is useful, show a compact plan. Group findings into:

    • safe to remove or archive
    • needs user review
    • protected or skipped
  6. Ask before changing files. Default to a dry run. Before deletion or archiving, show the exact paths and actions.

  7. Prefer recoverable archive over delete. Move approved files to .codex-cleanup/archive/<timestamp>/ and write a manifest with original path, size, modified time, and action. Permanent deletion should require explicit user wording.

  8. Verify after cleanup. Re-check git status or file inventory. Report only the meaningful result.

If the user wants recurring project-specific cleanup rules, suggest a small .workspace-hygiene.yml with keep/skip patterns. Do not create config files unless asked.

Categories

Safe cleanup candidates are usually untracked or ignored generated artifacts:

  • cache directories such as __pycache__, .pytest_cache, .mypy_cache, .ruff_cache, .parcel-cache, .turbo, .next/cache, node_modules/.cache
  • build/test outputs such as dist, build, coverage, htmlcov, test-results, playwright-report
  • temporary files such as *.tmp, *.bak, *.orig, *.rej, *.pyc, .coverage, log files in obvious log/output folders
  • agent/eval scratch outputs when the user confirms they are no longer needed

Needs review:

  • untracked source files, docs, spreadsheets, PDFs, notebooks, archives, local databases, datasets, screenshots, reports, and anything under data/
  • files modified recently, especially during the current task
  • large files with unclear provenance

Protected or skipped:

  • .git
  • .codex/skills and installed skill files
  • tracked files with modifications
  • .env, private keys, token files, credential stores, and secret-looking files
  • user-named keep paths

Safety Rules

  • Never delete or rewrite tracked changes unless the user explicitly asks for that exact action.
  • Never clean outside the resolved workspace root.
  • Never echo secret values. Report secret-looking paths only by path and category.
  • Treat databases, datasets, and archives as review-required even when they look generated.
  • Keep output in the user's language when possible.
  • Avoid large directory listings. Show counts and the top few largest or most relevant paths.

User-Facing Output

Use a short report by default:

Workspace cleanup plan
Root: <path>
Safe candidates: <count>, <size>
Needs review: <count>, <size>
Skipped/protected: <count>

Recommended action:
- Archive safe candidates to .codex-cleanup/archive/<timestamp>/
- Review these paths before touching them: ...

If the user wants action, ask for one concise confirmation unless they already gave explicit approval for the exact paths and action.