Agent skill

Inventory Content

by dandye in dandye/ai-runbooks

Systematic cataloging of information assets. An agent skill from dandye/ai-runbooks.

Apache-2.0Auto-check passedSecurity

Install Inventory Content

skills CLI
$ npx skills add dandye/ai-runbooks --skill inventory-content -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install dandye/ai-runbooks inventory-content --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/dandye/ai-runbooks.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/inventory-content .claude/skills/inventory-content && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
inventory-content
GitHub stars
127
Token cost
~621 tokens
SKILL.md length
262 words
Files
1
Skills in repo
27
Repo updated
First seen
Licence
Apache-2.0

At a glance

Systematic cataloging of information assets. An agent skill from dandye/ai-runbooks.

  • Works in 4 steps: Asset Discovery → Metadata Extraction → Format & Structure Analysis → …
  • Security work in your project
  • SKILL.md covers Inputs, Workflow, Required Outputs and Quick Reference
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Inventory Content is an agent skill from dandye/ai-runbooks. Systematic cataloging of information assets. Creates comprehensive inventories of all content with metadata and characteristics.

Its SKILL.md is about 620 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Security. The licence is Apache-2.0.

When your agent uses it

  • Security work in your project

Example prompts

  • “/inventory-content”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Asset Discovery
  2. Metadata Extraction
  3. Format & Structure Analysis
  4. Inventory Report Generation

What it can do on your machine

Read from SKILL.md and the folder at commit 72a6863. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Inventory Content loads about 621 tokens when it runs. Until then it costs about 37 tokens; SKILL.md has 262 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~37
When it runs · the whole SKILL.md, loaded when a task matches
~621

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from dandye/ai-runbooks at commit 72a6863, republished under its Apache-2.0 licence (© dandye). 262 words, ~621 tokens.

Download SKILL.mdSave it as .claude/skills/inventory-content/SKILL.md (or your agent's skills folder).
name
inventory-content
description
Systematic cataloging of information assets. Creates comprehensive inventories of all content with metadata and characteristics.
type
Skill
required_roles.scribe
roles/scribe.viewer
personas
information-architect, content-manager, librarian
generated.by
process:google-labs-jules
generated.at
2026-01-29T21:19:07Z

Content Inventory Skill

Create a systematic catalog of information assets within a specified path. This skill builds a comprehensive inventory including metadata, file characteristics, and format analysis to support content governance and strategic planning.

Inputs

  • PATH - The directory or file path to inventory (e.g., "/documentation")
  • OUTPUT_FORMAT - (Optional) The output format for the inventory, e.g., "csv", "json", "markdown" (default: "json")
  • METADATA_EXTRACTION - (Optional) Boolean, whether to extract deep metadata (author, date, tags) (default: true)
  • FORMAT_ANALYSIS - (Optional) Boolean, whether to analyze file formats and types (default: true)

Workflow

Step 1: Asset Discovery

Recursively scan the PATH to identify all files and assets.

  • Record file paths, names, and sizes.
  • Identify file types (Markdown, HTML, PDF, Image, etc.).
Step 2: Metadata Extraction

If METADATA_EXTRACTION is true, extract metadata from each asset:

  • System Metadata: Creation date, modification date, owner.
  • Embedded Metadata: Frontmatter (YAML), title headers, tags, categories.
  • Content Metrics: Word count, reading time estimation.
Step 3: Format & Structure Analysis

If FORMAT_ANALYSIS is true, analyze the structure:

  • Template Usage: Identify if standard templates are used.
  • Hierarchy Depth: Depth in the directory structure.
  • Resource Dependencies: Images or other assets linked.
Step 4: Inventory Report Generation

Compile the data into a structured inventory format (CSV, JSON, or Markdown Table) as specified by OUTPUT_FORMAT.

Required Outputs

A CONTENT_INVENTORY_REPORT in the specified OUTPUT_FORMAT containing:

  • Asset List: Full list of discovered assets.
  • Metadata Table: Columns for Title, URL/Path, Author, Last Modified, Type, Tags.
  • Summary Statistics: Total count by type, average age, volume by category.

Quick Reference

  • Purpose: Establish a baseline understanding of content assets for governance.
  • Use Case: Migration planning, audit preparation, consolidation projects.

© dandye, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/inventory-content of dandye/ai-runbooks.

Open the folder on GitHubat commit 72a6863

Compare with similar skills

Inventory Content next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Inventory Content compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Inventory Content this skilldandye/ai-runbooks127—~621Automated safety check: PassApache-2.0
Sentinelvinayaklatthe/microsoft-security-skills175—~2.2kAutomated safety check: PassMIT
Kubernetes Network Security Auditkubeshark/kubeshark12k—~7.3kAutomated safety check: NotesApache-2.0
Google Cloud PAM Helpergoogle/skills21k—~3.2kAutomated safety check: PassApache-2.0
Cyberowlaikarimhabush/cyberowl263—~2.5kAutomated safety check: PassMIT
DefectDojo Vulnerability ManagementAgentSecOps/SecOpsAgentKit220—~2.3kAutomated safety check: PassCustom licence

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Questions about Inventory Content

What does Inventory Content do?

Systematic cataloging of information assets. An agent skill from dandye/ai-runbooks. Inventory Content is an agent skill from dandye/ai-runbooks. Systematic cataloging of information assets.

When should I use Inventory Content?

Inventory Content fits situations like: security work in your project.

How do I install Inventory Content in Claude Code?

Run `npx skills add dandye/ai-runbooks --skill inventory-content -a claude-code`. Or copy the skill folder (skills/inventory-content in dandye/ai-runbooks) into .claude/skills/inventory-content in your project. Claude Code loads it when a task matches its description.

How do I install Inventory Content in Codex?

Run `npx skills add dandye/ai-runbooks --skill inventory-content -a codex`. Or copy the skill folder (skills/inventory-content in dandye/ai-runbooks) into .agents/skills/inventory-content in your project. Codex loads it when a task matches its description.

Can I use Inventory Content in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add dandye/ai-runbooks --skill inventory-content -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/inventory-content, .gemini/skills/inventory-content, .github/skills/inventory-content and .opencode/skills/inventory-content in your project.

What does Inventory Content need to run?

SKILL.md names no scripts, command-line tools or credentials: Inventory Content is instructions for the agent only.

Does Inventory Content access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Inventory Content safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Inventory Content use?

Inventory Content is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Inventory Content use?

About 621 tokens (SKILL.md is roughly 2.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Inventory Content?

Skills that share tags, products or a category with Inventory Content: Sentinel (vinayaklatthe/microsoft-security-skills, 175 stars), Kubernetes Network Security Audit (kubeshark/kubeshark, 12k stars), Google Cloud PAM Helper (google/skills, 21k stars) and Cyberowlai (karimhabush/cyberowl, 263 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Inventory Content?

dandye (a GitHub user) maintains it in dandye/ai-runbooks, which has 127 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on August 14, 2026.

Source: dandye/ai-runbooks on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.