agentleFS
maystudiosmaystudios/claude-skills/video-summarizer/SKILL.md

video-summarizer

Skill21 starsChanged 7 months agoMITView on GitHub

Analyzes local MP4 video files using the Gemini API and generates structured Markdown summaries. Supports custom prompts to extract specific information instead of the default summary. Use when the user wants to summarize, analyze, or extract key points from video files in bulk. Triggers on requests like "summarize my videos", "create markdown summaries for the videos", "analyze videos with Gemini", "generate video summaries", or "extract X from my videos". Requires GEMINI_API_KEY environment variable set in the system.

  • Reads credentials
  • Installs packages

2 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 3 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Check if the user provided a custom prompt or specific extraction instructions.

    line 26
  2. Distinctive:

    When the user invokes this skill:

    line 57
  3. Very specific:

    If the user specifies a custom prompt or extraction goal (e.g., "extract all tools mentioned", "summarize focusing on pricing", "list …

    line 59
  4. Very specific:

    If the user provides a prompt file path, pass it via --prompt-file path/to/file.txt.

    line 61
  5. Very specific:

    If the user gives no specific instructions, run without --prompt to use the default format.

    line 62
  6. Distinctive:

    If the user specifies a directory, pass it as the first positional argument.

    line 63

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Video Summarizer

Analyzes MP4 files in a directory via the Gemini API and writes a .md summary file next to each video.

Prerequisites

  • GEMINI_API_KEY env var must be set
  • google-genai installed: py -m pip install google-genai
  • Python available as py (Windows) or python3

Workflow

1. Determine the prompt

Check if the user provided a custom prompt or specific extraction instructions.

  • No custom prompt -> use the default (structured summary with Title, Summary, Key Points, Takeaways)
  • User provides custom instructions -> pass them via --prompt or --prompt-file

A custom prompt completely replaces the default. Examples of custom prompts:

  • "Extract all mentioned tools, their prices, and a one-line description for each"
  • "List every action item and deadline mentioned in this video"
  • "Create a transcript outline with timestamps"

2. Run the script

# Default summary — all videos in current directory (recursive)
py scripts/summarize_videos.py

# Default summary — specific directory
py scripts/summarize_videos.py "C:/path/to/videos"

# Custom prompt (inline) — replaces default summary format
py scripts/summarize_videos.py --prompt "Extract all product names and prices mentioned"

# Custom prompt (from file) — replaces default summary format
py scripts/summarize_videos.py --prompt-file my-prompt.txt

# Both directory and custom prompt
py scripts/summarize_videos.py "C:/path/to/videos" --prompt "List all key decisions made"

3. How Claude should handle user arguments

When the user invokes this skill:

  1. If the user specifies a custom prompt or extraction goal (e.g., "extract all tools mentioned", "summarize focusing on pricing", "list action items"), pass it via --prompt "...".
  2. If the user provides a prompt file path, pass it via --prompt-file path/to/file.txt.
  3. If the user gives no specific instructions, run without --prompt to use the default format.
  4. If the user specifies a directory, pass it as the first positional argument.

4. Default output format (when no custom prompt is given)

# [Video Title]

## Summary
[2-3 sentence description]

## Key Points
- point 1
- point 2
- ...

## Core Content & Takeaways
[Central message and key insight]

---
*Auto-generated with Gemini API*

Notes

  • Language of the summary matches the language of the video
  • Files are auto-deleted from Gemini storage after processing (48h limit)
  • Already-summarized videos are skipped on re-runs
  • Script path: scripts/summarize_videos.py
  • Model: gemini-3-flash-preview

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.