Render Value Prop

OrganizationPopular

gooseworks-ai

render-value-prop

Render a designed 'value prop' video from a config — 3-5 noun-phrase benefit claims (<=4 words each) revealed sequentially over per-SKU product visuals, one crisp editorial frame per claim (hook sticker -> N claim beats -> brand end card). Deterministic PIL/HTML beat renderer frame-stepped via Playwright and encoded with FFmpeg, sound-off legible, hard cuts, uniform pacing. FREE (no paid calls); music is added separately (create-music-elevenlabs). Use for the value-prop format.

Overview

Publisher	gooseworks-ai
Repository	`goose-skills`
Skill name	`render-value-prop`
Stars	1.2K
Forks	208
Bundled files	23
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.
23 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 Value Prop 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-value-prop

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-value-prop .claude/skills/render-value-prop

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

Use it in TypingMind

Enable Render Value Prop 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 Value Prop 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 Value Prop 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-value-prop

Render a designed 'value prop' video from a config: a hook sticker, then one beat per short noun-phrase benefit claim (<=4 words each — "Drug-Free", "Zero Sugar", "NSF Certified"), each pairing the claim headline with a per-SKU product visual (the hero SKU rotates beat to beat so the eye anchor shifts), then a brand-wordmark end card. Text + product carry the spot — no narration, no talking head — and it is built to be legible sound-off. Every beat is a pure function of beat-local time t (deterministic PIL start frames + Playwright hyperframes + FFmpeg); no CSS keyframes, no setTimeout. FREE (no paid calls); music is a separate capability (create-music-elevenlabs), or ship silent for $0.

Run

render_master.py --config config.json --project <dir> -> <dir>/finals/master-clean.mp4 (silent), 1080x1920, deterministic, $0. The renderer is fully config-driven — palette, copy, SKUs, pacing, hook, logo and end card all come from config.json (schema = ad_sample.recipe.config; see config.example.json). Nothing is hardcoded to one brand. build_storyboard_preview.py is an optional free preview gallery for the gate; build_text_overlays.py is optional (transparent text-zone PNGs for compositing claims over a motion clip).

Environment: run with a Python that has Playwright (override the frame-render interpreter with RENDER_PYTHON); ffmpeg is auto-discovered (FFMPEG env > PATH > common prefixes). The frame renderer render_hyperframe.py is bundled in scripts/ — no external atom to fetch.

Contract

Deterministic + FREE (Playwright frame-step + FFmpeg); no paid calls, no AI-rendered text.
Claims are noun phrases, <=4 words; never <3, never >5. Optional benefit sentence <=12 words.
One product visual per beat; rotate which SKU is the hero. Never reuse a flat variety-pack image as every canvas.
Sound-off legibility is the bar: the headline uses the config palette.ink color on palette.bg; the per-beat accent color (from value_props[].accent — a SKU-accent slug or a hex) is the accent rule, not the headline.
Product widths auto-scale from each image's aspect ratio (target display height), so tall sachet cutouts and wide product packshots both frame correctly.
Assets are packshots, not always transparent cutouts: set palette.bg to the product image's background color for seamless compositing (free — avoids a paid background-removal step).
Uniform pacing (hook ~3.0s, props 2.0-2.5s each, endcard ~2.0s); total lands in the 10-20s window (~17s). No acceleration curve.
No human face is the focus. End card uses the brand wordmark image when a hi-res one (aspect >= ~1.2, i.e. a real >=1200x600 wordmark) is provided via config.logo; otherwise it falls back to a typographic brand_name wordmark (many brands ship only a favicon).
Music is added separately by create-music-elevenlabs (quiet instrumental bed at -14 dB), or ship silent.

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 Value Prop AI skill do?

Why use Render Value Prop on TypingMind?

Because you install it once and use it with any model. Render Value Prop 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 Value Prop 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-value-prop. 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 Value Prop?

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 Value Prop?

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

Is the Render Value Prop 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.

View all

Design Html

garrytan

CommunityPopular

Design finalization: generates production-quality Pretext-native HTML/CSS. (gstack)

Design Shotgun

Design shotgun: generate multiple AI design variants, open a comparison board, collect structured feedback, and iterate. (gstack)

Diagram

Turn an English description (or mermaid source) into a diagram triplet: the source, an editable .excalidraw file you can open on excalidraw.com, and rendered SVG + PNG. (gstack)

Office Hours

YC Office Hours — two modes. (gstack)

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

render-value-prop

Run

Contract

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now