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Watch

OrganizationPopular
gooseworks-ai
watch

Watch a rendered video (whole file or specific ranges) at a chosen fidelity and emit a timestamp-keyed observation report. Observation only — no edits, no verdicts.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill namewatch
Stars
1.2K
Forks
216
Bundled files
7
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.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Watch 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/gooseworks-ai/goose-skills/tree/main/skills/ads/packs/video-ad-formats/watch
  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/gooseworks-ai/goose-skills.git /tmp/goose-skills
mkdir -p .claude/skills
cp -r /tmp/goose-skills/skills/ads/packs/video-ad-formats/watch .claude/skills/watch
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Watch 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 Watch 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 Watch 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.

watch

Purpose

Look at a rendered video and report what is actually on screen and in the audio. By default it watches the entire video and considers visuals, voiceover, music, and sound effects. Callers can narrow the scope (specific timestamp ranges, lower frame rate, disable audio tracks) when they want a cheaper or more focused pass.

This is the observation primitive that watch-and-refine calls before deciding what to fix. Other review and editing skills can call it directly.

Watch every assembled generated video at up to 2 fps. Real-time playback smooths over what frames show plainly: a half-second face flash, a wardrobe pop at a cut, a frozen scene, an invented background element.

Inputs

  • video — path to a local video file. Required.
  • ranges — optional list of [start, end] timestamps to watch. Accepts SS, MM:SS, or HH:MM:SS. Defaults to the whole video.
  • fps — frame sampling rate. Defaults to auto by duration (≤30s → 1–2 fps, 30s–1min → ~1 fps, 1–3min → ~0.5 fps, 3–10min → ~0.25 fps). Hard cap 2 fps.
  • max_frames — hard cap on total frames sampled across all ranges. Default 100.
  • resolution — frame width in px. Default 512. Bump to 1024 only when on-screen text legibility matters.
  • include_voice — bool, default true. Transcribe spoken VO/dialogue.
  • include_music — bool, default true. Describe music presence, swells, drops, gain relative to VO.
  • include_sfx — bool, default true. Note sound effects, foley, transition stingers.
  • focus — optional free-text prompt describing what to pay attention to (e.g. "watch the end card", "judge cut timing on the beat drop").

If all three audio flags are false, the skill runs frames-only and notes this in the manifest.

Workflow

  1. Validate video exists and is readable. Probe duration with ffprobe.
  2. Resolve ranges: if empty, use [0, duration]. Reject ranges outside the file duration.
  3. Resolve fps: use caller value if provided, else auto-scale from total resolved range duration. Clamp at 2 fps.
  4. Allocate the max_frames budget across ranges proportionally to range duration.
  5. Extract frames with ffmpeg into frames/ at the resolved fps and resolution.
  6. If any audio flag is true, extract the audio for the resolved ranges to a working WAV. Run a transcript pass when include_voice=true; degrade to frames-only and flag a warning if no Whisper backend is available.
  7. Compose observation.md — a timestamp-keyed report. Each entry references the frame paths visible during that window plus any transcript line and audio notes (music/SFX) for the same window. If focus is set, lead each entry with what was observed about that focus.
  8. Write manifest.json capturing the resolved inputs (ranges, fps, frame count, audio flags) and output paths.

Output

  • observation.md — timestamp-keyed observation report. No verdicts, no "good/bad" framing.
  • frames/*.jpg — sampled frames referenced from the report.
  • transcript.json — word-timestamped transcript, only when include_voice=true and a Whisper backend was available.
  • manifest.json — resolved inputs and output paths.

Quality Checks

  • Frame count never exceeds max_frames.
  • Every range produced at least one frame, unless the range is shorter than 1 / fps.
  • When include_voice=true, the transcript covers the resolved ranges (no >500ms gap inside a VO segment unless the audio itself is silent there).
  • All paths in manifest.json resolve to real files.
  • The report contains no recommendations — it describes only what was observed.

Failure Modes

  • Missing or unreadable video.
  • A ranges entry falls outside the file duration.
  • include_voice=true but no Whisper backend is configured — degrade to frames-only and flag a warning in the manifest.
  • max_frames budget too tight to give every range at least one frame — surface which ranges were skipped.

References

  • references/parameters.md — full parameter reference, defaults, and the auto-fps budget table.

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 Watch AI skill do?

Watch a rendered video (whole file or specific ranges) at a chosen fidelity and emit a timestamp-keyed observation report. Observation only — no edits, no verdicts.

Why use Watch on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/packs/video-ad-formats/watch. 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 Watch?

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 Watch?

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

Is the Watch AI skill free?

Yes. It is published on GitHub by gooseworks-ai 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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