Organize Workspace

Community

danielvm-git

organize-workspace

Scans the active workspace for disposable artifacts—logs, caches, stale build output, and stray draft markdown—and proposes consolidation of scattered assets. Produces a reviewable list, asks for explicit confirmation before any delete or move, and optionally revises .gitignore. Use when the user says "clean my room", "organize workspace", "workspace cleanup", "remove temp files", "organize assets", "gitignore", or wants a safe tidy pass.

Overview

Publisher	danielvm-git
Repository	`bigpowers`
Skill name	`organize-workspace`
Stars	206
Forks	18
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by danielvm-git on GitHub. Read the source before you install it.

Installation

Install the Organize Workspace AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/danielvm-git/bigpowers.git /tmp/bigpowers
mkdir -p .claude/skills
cp -r /tmp/bigpowers/skills/organize-workspace .claude/skills/organize-workspace

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Organize Workspace in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Organize Workspace on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Organize Workspace is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Organize Workspace

HARD GATE — HARD GATE — Workspace structure must reflect domain structure. If the codebase feels disorganized, flag it. Disorganization != 'just a style thing;' it is a signal of domain misalignment.

Principles

Read-only first: inventory and size (du, ls -la) before any change.
Never delete or move without a numbered list and explicit user approval (item-level or "approve all").
Prefer fd / ripgrep / find in that order; avoid blind rm -rf on vague globs.
Do not touch .git/, node_modules/, venv/, .env*, or SSH keys; flag them only if the user asked about them.
Confirm prompts in the user's language if they are not writing in English.

1. Establish scope

Default: current project root (where the user is working) or the path they name.
Record OS (macOS vs Linux) for ignore patterns (e.g. .DS_Store).

2. Classify candidates (scan)

Group findings under these buckets:

Bucket	Examples	Typical action
Logs & temp	`.log`, `logs/`, `tmp/`, `temp/`, `.pid`	Delete after confirm
Build / cache	`dist/`, `build/`, `.next/`, `coverage/`, `.turbo/`	Delete if rebuildable
Package caches	root `.cache/`, `__pycache__/`	Offer delete
Stray drafts	root-level `*.md` named `draft`, `scratch`, `temp`	User picks: delete, move to `specs/`, or keep
Duplicate / dump dirs	`old/`, `backup/`, `copy/`, `*_backup`	List + ask

Use quick size hints: du -sh per top-level dir; sort large items first.

3. Assets & data (organize, not only delete)

If the user wants organization:

Propose a single convention, e.g.:
- assets/ — images, fonts, static media
- data/ — JSON, CSV, fixtures, samples
- specs/ — all planning and domain documents
For each cluster of loose files, suggest one target path and a short rationale.
Use git-aware moves when in a repo: git mv if tracked; otherwise mv and report.
Never move secrets or production DB dumps into docs/ or public assets/.

4. Present the plan

Output a table or numbered list:

Path
Kind (log / build / draft / asset / other)
Approx size
Proposed action: delete | move to … | keep

Ask: "Delete items 1–3? Move 4–5? Skip 6?"

5. Execute after approval

Deletes: on macOS, prefer a Trash-capable tool (e.g. trash from Homebrew) if installed; else rm with paths echoed back.
Moves: create dirs with mkdir -p first; one batch at a time.
Verify: re-run listing on affected parents; if anything failed, report stderr.

6. Post-cleanup and `.gitignore` revision

Do this when the repo is under Git and the cleanup surfaced untracked noise:

Inventory ignore sources: root .gitignore, .git/info/exclude, any subpackage .gitignore files.
Map findings to rules: for each deleted or recurring artifact class, check whether a pattern already exists; note gaps.
Propose a patch: list only concrete changes — + add / - remove / ~ reword — with one-line why.
User must approve the exact diff before editing the file.
Verify: run git check-ignore -v <path> on 2–3 representative paths.

See REFERENCE.md for shell patterns, .gitignore mechanics, and safety checks.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

REFERENCE.md3 KB

Frequently asked questions

What does the Organize Workspace AI skill do?

Why use Organize Workspace on TypingMind?

Because you install it once and use it with any model. Organize Workspace is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Organize Workspace in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/danielvm-git/bigpowers/tree/main/skills/organize-workspace. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Organize Workspace?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Organize Workspace?

As many as you like. As long as a model supports skills, you can use Organize Workspace with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Organize Workspace AI skill free?

Yes. It is published on GitHub by danielvm-git under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Organize Workspace

Principles

1. Establish scope

2. Classify candidates (scan)

3. Assets & data (organize, not only delete)

4. Present the plan

5. Execute after approval

6. Post-cleanup and .gitignore revision

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now

6. Post-cleanup and `.gitignore` revision