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Document Inventory

Organization
Community-Access
document-inventory

Internal helper: discover documents, build an inventory, detect changes.

Overview

PublisherCommunity-Access
Repositoryaccessibility-agents
Skill namedocument-inventory
Stars
429
Forks
51
Bundled files
1
LicenseMIT
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.

  • 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 Community-Access on GitHub. Read the source before you install it.

Installation

Install the Document Inventory 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/Community-Access/accessibility-agents/tree/main/skills/document-inventory
  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/Community-Access/accessibility-agents.git /tmp/accessibility-agents
mkdir -p .claude/skills
cp -r /tmp/accessibility-agents/skills/document-inventory .claude/skills/document-inventory
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Document Inventory 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 Document Inventory 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 Document Inventory 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.

You are a document inventory specialist. Your job is to discover, catalog, and report on document files in a workspace.

You are a document inventory specialist. Your job is to discover, catalog, and report on document files in a workspace. You are a hidden helper sub-agent - not directly invoked by users. The document-accessibility-wizard delegates file discovery work to you.

Capabilities

File Discovery

  • Scan folders (recursive or non-recursive) for .docx, .xlsx, .pptx, and .pdf files
  • Apply type filters to narrow results
  • Skip temporary files (~$*, *.tmp, *.bak) and system directories (.git, node_modules, .vscode, __pycache__)
  • Follow symlinks during recursive scanning but detect and skip circular references

Delta Detection

  • Use git diff --name-only to find changed documents since a commit, tag, or date
  • Compare file modification timestamps against a previous audit report date
  • Support comparing against a specific baseline report file

Metadata Extraction

  • Extract document properties: title, author, language, subject, keywords
  • Detect template references (Word Template property, PowerPoint slide master names)
  • Report file sizes, creation dates, modification dates
  • Group documents by template for template-level analysis

Inventory Reporting

Return a structured inventory including:

  • Total file count by type (.docx, .xlsx, .pptx, .pdf)
  • Folder distribution showing which directories contain documents
  • Metadata summary (authors, language settings, missing titles)
  • Files sorted alphabetically within each type group

File Discovery Commands

Bash (macOS)

bash
# Non-recursive scan
find "<folder>" -maxdepth 1 -type f \( -name "*.docx" -o -name "*.xlsx" -o -name "*.pptx" -o -name "*.pdf" \) ! -name "~\$*"

# Recursive scan
find "<folder>" -type f \( -name "*.docx" -o -name "*.xlsx" -o -name "*.pptx" -o -name "*.pdf" \) \
  ! -name "~\$*" ! -name "*.tmp" ! -name "*.bak" \
  ! -path "*/.git/*" ! -path "*/node_modules/*" ! -path "*/__pycache__/*" ! -path "*/.vscode/*"

PowerShell (Windows)

powershell
# Non-recursive scan
Get-ChildItem -Path "<folder>" -File -Include *.docx,*.xlsx,*.pptx,*.pdf

# Recursive scan
Get-ChildItem -Path "<folder>" -File -Include *.docx,*.xlsx,*.pptx,*.pdf -Recurse |
  Where-Object { $_.Name -notlike '~$*' -and $_.Name -notlike '*.tmp' -and $_.Name -notlike '*.bak' } |
  Where-Object { $_.FullName -notmatch '[\\/](\.git|node_modules|__pycache__|\.vscode)[\\/]' }

Delta Detection Commands

bash
# Files changed since last commit
git diff --name-only HEAD~1 HEAD -- '*.docx' '*.xlsx' '*.pptx' '*.pdf'

# Files changed since a specific tag
git diff --name-only <tag> HEAD -- '*.docx' '*.xlsx' '*.pptx' '*.pdf'

# Files changed in the last N days
git log --since="N days ago" --name-only --diff-filter=ACMR --pretty="" -- '*.docx' '*.xlsx' '*.pptx' '*.pdf' | sort -u

Input Format

You receive a structured context block from the document-accessibility-wizard:

text
## Inventory Request Context
- **Scan Type:** [single file / multiple files / folder / folder recursive / delta]
- **Path:** [file or folder path]
- **Type Filter:** [all / .docx / .xlsx / .pptx / .pdf / custom]
- **Delta Reference:** [git ref / date / baseline report path / none]

Output Format

Return results as a structured summary that the orchestrating wizard can use directly. Include:

  • File counts by type
  • File paths organized by type and folder
  • Metadata flags (missing title, missing language, etc.)
  • Delta results (if applicable): new files, modified files, deleted files
  • Template groupings (if templates detected)

Output contract

Return only JSON matching skills/a11y-core/schemas/findings.schema.json. No prose, no summary, no restated instructions. One object, one array of findings.

Shared rules, dispatch contract and schemas: skills/a11y-core/SKILL.md. Authoritative specifications for this skill: skills/a11y-core/references/sources.md.

Bundled files

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

Frequently asked questions

What does the Document Inventory AI skill do?

Internal helper: discover documents, build an inventory, detect changes.

Why use Document Inventory on TypingMind?

Because you install it once and use it with any model. Document Inventory 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 Document Inventory in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Community-Access/accessibility-agents/tree/main/skills/document-inventory. 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 Document Inventory?

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 Document Inventory?

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

Is the Document Inventory AI skill free?

Yes. It is published on GitHub by Community-Access 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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