Investment Folder Organizer logo

Investment Folder Organizer

Community
latour-ai
investment-folder-organizer

Organize a messy folder of investment files into a clean, standardized subfolder structure and rename every file with a consistent, sortable convention. Use this skill whenever the user points at a folder of deal or diligence files and wants it tidied, sorted, structured, or renamed — for a hedge fund (allocator), a public security, a private company (PE buyout), or a startup (VC). Trigger on phrases like "organize this deal folder," "clean up these diligence files," "sort and rename these documents," "structure my data room," "put these investment files in order," "organize this fund's folder," or when the user shares a folder path full of pitch decks, CIMs, financials, DDQs, term sheets, letters, or memos and wants it made navigable. Works on a local filesystem and is non-destructive — it copies originals into a new organized folder, never moves or deletes. Do NOT use for organizing non-investment folders (photos, code repos, personal documents).

Overview

Publisherlatour-ai
Repositoryskills
Skill nameinvestment-folder-organizer
Stars
69
Forks
4
Bundled files
Instructions only
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by latour-ai on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/latour-ai/skills/tree/main/investment-folder-organizer
  4. 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.
2

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/latour-ai/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/investment-folder-organizer .claude/skills/investment-folder-organizer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Investment Folder Organizer 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 Investment Folder Organizer 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 Investment Folder Organizer 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.

Investment Folder Organizer

Turn a chaotic pile of investment files into a clean, predictable structure: eight standardized subfolders plus a consistent, date-first filename convention, with a generated index that doubles as an audit trail. Same structure for every investor type — allocator, public-equity, PE, or VC — so the layout is learnable once and reused forever.

Non-destructive by design: originals are never moved or deleted. Files are copied into a new sibling folder. If the user explicitly asks to move/replace in place, confirm that intention before doing anything irreversible.

Workflow

1. Locate and scope the folder

Confirm the source folder path. If the user hasn't given one, ask. Then inventory everything, including nested subfolders — these get flattened into the new structure. List files with their type and size:

bash
find "<source_folder>" -type f -not -name '.*' -printf '%P\t%s bytes\n' | sort

Note the likely investor context (fund / public co / private co / startup) from the filenames and the user's framing — it informs DocType choices but not the folder structure, which is always the same eight folders.

2. Read enough of each file to classify it

Classify on content first, filename second — investment files are notoriously mislabeled (Project Atlas v3 FINAL.pdf could be anything). You usually do not need the whole file; the first page / first slide / first sheet plus the filename is typically decisive. Read more only when torn.

  • PDFs: read the first page or two (text or rasterize). For PDF reading strategy see the pdf-reading skill if available.
  • Office files (.docx/.pptx/.xlsx): use the relevant skill (docx, pptx, xlsx) or extract text; the title slide, document heading, or first sheet usually suffices.
  • For other types and a routing cheat-sheet, consult the file-reading skill.
  • Sample large files — don't burn context reading a 300-page data dump end to end.

Read references/taxonomy.md for the folder definitions, the content-based classification tie-breakers (e.g. Marketing vs. Research, Financials vs. Legal), and the full DocType vocabulary. Consult it whenever a placement is non-obvious.

3. Build the plan

For every file, decide three things: which of the eight folders, the new filename, and a confidence level. Assemble them into a plan JSON (schema in the script header and below). Set confidence to medium/low and add a one-line note for anything you're unsure about; route genuinely unclassifiable files to 99_Unsorted. These get surfaced in the index for the user to review, which is far better than a confident misfile.

The eight folders (defined fully in references/taxonomy.md):

FolderHolds
01_Overview_and_MarketingWhat the target produced to present itself: decks, CIMs, tear sheets, teasers
02_FinancialsStatements, models, projections, cap tables, track record, 10-K/10-Q
03_Due_DiligenceDDQs, ODD/DD reports, reference & background checks
04_Legal_and_ComplianceLPAs, term sheets, SPAs, SAFEs, NDAs, ADV, proxies
05_Research_and_AnalysisIC/deal memos, theses, valuation work, market & expert research
06_CommunicationsInvestor letters, founder updates, call transcripts, meeting notes, emails
07_ReferenceBios, org charts, background, press
99_UnsortedAnything not confidently classified

Naming: YYYY-MM-DD_DocType_Descriptor.ext — date first (use the content date, fall back to file mtime), PascalCase DocType, short hyphenated descriptor, no company/fund name (the parent folder carries it). Full rules and examples are in references/taxonomy.md.

4. Preview, then execute

Show the user a compact summary of the plan before copying — counts per folder and, critically, any files headed to 99_Unsorted or flagged low-confidence. Invite a quick correction. For a small set you can list every rename; for a large set, show the per-folder counts plus the flagged items and a handful of representative renames.

To preview mechanically without copying, run the script with --dry-run.

Write the plan to a JSON file, then run the executor. By default the output folder is a sibling named <SourceName> (Organized):

bash
python scripts/organize.py --plan /path/to/plan.json
# add --dry-run first if you want a no-write preview

The script handles the deterministic, error-prone parts so you don't have to: canonicalizing folder names, sanitizing filenames, preserving extensions, resolving name collisions (-2, -3, …), copying with copy2, and writing 00_INDEX.md.

5. Present the result

Point the user to the new folder and 00_INDEX.md. Explicitly call out the Needs review section — the unsorted and low-confidence files — and offer to re-file any of them based on the user's steer. If they correct a placement, edit the plan and re-run (re-running into a fresh output folder is cheap and clean).

Plan JSON shape

json
{
  "source_root": "/abs/path/to/messy/folder",
  "output_root": "/abs/path/to/Target (Organized)",
  "subject": "Acme Capital — Flagship Fund",
  "investor_context": "hedge fund allocator",
  "items": [
    {
      "source": "subdir/Q3 letter FINAL.pdf",
      "folder": "06_Communications",
      "new_name": "2024-09-30_InvestorLetter_Q3-2024.pdf",
      "confidence": "high",
      "note": ""
    }
  ]
}
  • source is relative to source_root (absolute paths also accepted).
  • folder accepts the canonical name or a short alias (Financials, 02, legal…); unknown values are routed to 99_Unsorted and flagged.
  • confidence is high | medium | low (default high).
  • note is optional but always shown in the index for unsorted/low/medium items.

Principles

  • Never destructive. Copy. Leave the original folder untouched unless the user explicitly and knowingly asks otherwise.
  • Content over filenames. The whole point is to fix bad names, so don't trust them.
  • Flag, don't guess. A file in 99_Unsorted with a note beats a confident misfile.
  • One structure, every asset class. Don't fork the taxonomy per investor type; adapt only the DocType words.

Frequently asked questions

What does the Investment Folder Organizer AI skill do?

Organize a messy folder of investment files into a clean, standardized subfolder structure and rename every file with a consistent, sortable convention. Use this skill whenever the user points at a folder of deal or diligence files and wants it tidied, sorted, structured, or renamed — for a hedge fund (allocator), a public security, a private company (PE buyout), or a startup (VC). Trigger on phrases like "organize this deal folder," "clean up these diligence files," "sort and rename these documents," "structure my data room," "put these investment files in order," "organize this fund's fol...

Why use Investment Folder Organizer on TypingMind?

Because you install it once and use it with any model. Investment Folder Organizer 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 Investment Folder Organizer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/latour-ai/skills/tree/main/investment-folder-organizer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Investment Folder Organizer?

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 Investment Folder Organizer?

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

Is the Investment Folder Organizer AI skill free?

It is published on GitHub by latour-ai. Check the repository for licensing terms. 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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