Render Proof Points Overlay

OrganizationPopular

gooseworks-ai

render-proof-points-overlay

Build the deterministic PIL pill overlays for a 'perfect-score + proof-points' UGC video ad (white 10/10 score header with a medal + orange sub with a finger-down + 3-4 green-check proof pills) and composite them onto a base clip in a diagonal L->R->L->R cascade, then mux the music bed into master-final.mp4. Config-driven (config.json), 1080x1920 9:16, FREE and deterministic (no paid calls, text stays pixel-crisp). Use for the overlay-proof-points format; the base clip + music come from separate paid capabilities.

Overview

Publisher	gooseworks-ai
Repository	`goose-skills`
Skill name	`render-proof-points-overlay`
Stars	1.2K
Forks	208
Bundled files	5
License	MIT
Links	Skill source Repository Homepage

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.
5 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 Render Proof Points Overlay AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-proof-points-overlay

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/render-proof-points-overlay .claude/skills/render-proof-points-overlay

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Render Proof Points Overlay 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 Render Proof Points Overlay 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 Render Proof Points Overlay 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.

render-proof-points-overlay

Build the deterministic PIL/FFmpeg overlays for the "Instagram comparison-tool reviewer" UGC ad — a white "we got a perfect 10/10 score" headline pill (trailing medal), an orange "but here's also why you'll love us" sub pill (trailing finger-down, width-matched to the header), and 3-4 green-check proof pills — then composite them onto a base clip in the format's signature diagonal cascade and mux the music into the master. FREE and deterministic: the pills are PIL-rendered so the score, checks, and wordmark stay pixel-crisp (a video model would smear type). The base clip (create-image-fal keyframe -> create-video-fal i2v) and the music bed (create-music-elevenlabs) come from separate paid capabilities; this one only does the free rendering.

Run

fetch_icons.py --run-dir ; build_overlays.py --config config.json --out-dir /generated/overlays ; compose_master.py --config config.json --run-dir — reads /generated/clip-handheld.mp4 + generated/music-bed.m4a, writes /master-final.mp4. 1080x1920, deterministic, $0. (Add --no-music to compose for a silent design preview.)

Scripts

fetch_icons.py — downloads the three Twemoji PNGs (medal 1f3c5, finger-down 1f447, check 2705) to <run>/assets/icons. PIL cannot render Apple Color Emoji, so pills paste Twemoji PNGs. Free, local.
build_overlays.py — PIL: renders the white score header (trailing medal), the orange subhead (trailing finger-down, width-matched to the header), and N green-check proof pills auto-sized to their copy. Bold weight and icon-centered-on-pill-middle are load-bearing.
compose_master.py — FFmpeg: scale/crop the base clip to 1080x1920@30, composite the always-on headers, cascade the proof pills (each enable='gte(t,T)' on its own alternating LEFT/RIGHT row), mux the music, apply the anti-AI grain pass, re-encode crf23/maxrate12M -> master-final.mp4.

Contract

Deterministic + FREE (PIL + FFmpeg); no paid calls, no AI-rendered text — the score, checks, and wordmark are composited, never generated.
Config-driven off one config.json (overlays, layout, duration_sec, optional music/post_production); the template recipe supplies the config from recipe.config.
Always re-run build_overlays.py before compose_master.py — the compositor reads pre-rendered PNGs and silently reuses stale ones on a copy change.
Headers stay on 0-duration and must not cover the bottle face; proof pills cascade one-per-beat down the diagonal (NOT four-corners) — the cascade is the format's signature.
Requires Pillow + ffmpeg. No API keys.

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 Render Proof Points Overlay AI skill do?

Why use Render Proof Points Overlay on TypingMind?

Because you install it once and use it with any model. Render Proof Points Overlay 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 Render Proof Points Overlay in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-proof-points-overlay. 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 Render Proof Points Overlay?

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 Render Proof Points Overlay?

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

Is the Render Proof Points Overlay 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

render-proof-points-overlay

Run

Scripts

Contract

Bundled files

Frequently asked questions

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