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Caption Burn

OrganizationPopular
gooseworks-ai
caption-burn

Burned-in captions for a finished vertical video, three kinds. transcribe.py gets word timings from the video's own audio through the GooseWorks proxy (fal Whisper, bills the Ads agent, cents); captions.py burns one to three words at a time with Pillow + ffmpeg (no libass needed), either pinned to a split-screen seam (plate 25% above / 75% below) or at a fixed height, in a plate, outline or one-word serif style, with an optional red hook card; plates.py burns per-beat caption blocks (black, one union silhouette, placed in the emptiest band) for formats with no voice. The last caption (the CTA) holds to the final frame. Use as the last step of any video ad.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill namecaption-burn
Stars
1.2K
Forks
216
Bundled files
8
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.

  • 8 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 Caption Burn 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/capabilities/caption-burn
  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/capabilities/caption-burn .claude/skills/caption-burn
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Caption Burn 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 Caption Burn 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 Caption Burn 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.

Superseded: the video kit now does this with the captions-layer part, version 1.1.0, in the parts folder of this repository. It burns the same plate captions from the speech timings, holds the last caption to the end, transcribes only when there are no timings, and returns a WebVTT of what it drew. This atom stays, unchanged in behaviour, for skills outside the kit until they move; its scripts still run.

caption-burn

Captions timed to what is actually said in the finished video, not to the script's estimate.

Run

bash
python transcribe.py --media reel.mp4 --out reel.words.json          # paid, cents
python captions.py --video reel.mp4 --beats cutlist.aligned.json \
    --words reel.words.json --out final.mp4 [--style plate|outline] [--highlight Brand]

--beats supplies the lines (vo), their timing and, for split layouts, seam, size and each beat's state. Any file with beats: [{start, end, vo}] works.

Placement and style

  • --anchor seam (the default when the beats have a seam): on split beats the plate is pinned to the seam, positioned by the plate, not the text: 25% of the plate above the line, 75% below. Full-frame beats use --full-y.

  • --anchor fixed --y 0.62: every caption's plate centred at that fraction of the height.

  • plate (default): white bold on a dark grey rounded plate, 1–2 words, cap ~0.019 H.

  • outline: white bold with a dark outline, no plate, 1–3 words, cap ~0.034 H.

  • --highlight WORD colours that word yellow (the CTA keyword). Repeatable.

  • serif-word: ONE word at a time, heavy serif (Georgia Bold), white with a black outline, on a fixed baseline at 0.77 H (the screen-insert look). The highlight word is quoted.

  • --card "LINE ONE|LINE TWO" --card-until 4.7: a white rounded hook card with two lines of heavy red capitals near the top, for the opening seconds. ~14 characters a line.

Captions for a format with no voice (plates.py)

bash
python plates.py --video walk.mp4 --beats cutlist.json --out captioned.mp4 [--logo logo.png]

Each beat's caption (a string or list of lines) shows for the whole beat on ONE black block (square rectangles unioned, then rounded as a single silhouette: rounding each line leaves seams), lines left-aligned, the block centred on its widest line. It goes in the emptiest band of that beat's frame unless the beat pins cap_y. logo: true on a beat hangs the logo tile under the block. Write lines a person would type: the same short "fragment. fragment." shape three times reads as AI-written. No emoji twice.

Rules

  1. Transcribe the FINISHED audio. Joining takes and aligning lines shifts timing; only the final video's audio gives correct cues.
  2. The last caption holds to the last frame. It is the call to action.
  3. A word Whisper writes differently ("200" for "two hundred") is interpolated between its neighbours rather than dropped or stretched over the whole line.
  4. Without --words timing is estimated from syllables. Use that to judge placement, never to ship.
  5. Fonts: a bold sans is found on macOS, Linux or Windows; if none is present, Roboto Bold is fetched once into ~/.cache/gooseworks/fonts. --font or GW_CAPTION_FONT overrides.

Footprint before composition

The bundled footprint helper uses this renderer's cue grouping, selected font, stroke, plate padding and anchor. Export it from the approved beat list and pass it to the footage-cutlist preview. The JSON includes every group and the union of its rendered bounds per beat. Use the same style, anchor, font and fixed-position settings for the final burn; regenerate after alignment or copy changes. Caption coverage must leave claim qualifications readable. Inspect final captioned frames as well as this planned coverage.

Pass the same highlight terms to footprint and burn, including serif-word quotes. Preview rejects a changed cut list until its footprint is rebuilt. An explicitly supplied missing font fails in both commands.

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 Caption Burn AI skill do?

Burned-in captions for a finished vertical video, three kinds. transcribe.py gets word timings from the video's own audio through the GooseWorks proxy (fal Whisper, bills the Ads agent, cents); captions.py burns one to three words at a time with Pillow + ffmpeg (no libass needed), either pinned to a split-screen seam (plate 25% above / 75% below) or at a fixed height, in a plate, outline or one-word serif style, with an optional red hook card; plates.py burns per-beat caption blocks (black, one union silhouette, placed in the emptiest band) for formats with no voice. The last caption (the C...

Why use Caption Burn on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/caption-burn. 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 Caption Burn?

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 Caption Burn?

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

Is the Caption Burn 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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