mcpbeat Sign in

Render Value Prop Agent Skill

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.

20k tokens
context cost
the whole folder, loaded on every use
24
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
1086
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/gooseworks-ai/goose-skills --skill render-value-prop

What comes with it

76 119 bytes besides the instruction
scripts/build_storyboard_preview.py
scripts/build_text_overlays.py
scripts/config.example.json
scripts/render_hyperframe.py
scripts/render_master.py
shared/_shared.css
shared/_shared.js
shared/animations/registry.yml
shared/animations/sachet-entrance/cascade-from-top.js
shared/animations/sachet-entrance/fade-stagger.js
shared/animations/sachet-entrance/slide-in-lateral.js
shared/animations/sachet-entrance/springScale-pop.js
shared/animations/sachet-entrance/tilt-fan.js
shared/animations/text-entrance/fade-stagger.js
shared/animations/text-entrance/mask-reveal.js
shared/animations/text-entrance/type-on.js
shared/animations/text-entrance/word-by-word.js
shared/beat-templates/endcard-wordmark.html
shared/beat-templates/hook-sticker.html
shared/beat-templates/prop-hero.html
shared/beat-templates/prop-row.html
skill.meta.json
tests/smoke-test.md

The instruction itself

3 sections, as written by the author

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.

Other skills for the same job

different authors, same section of the catalogue
Canvas Design
by anthropics
vendor ×13

Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

1388k tokens
Algorithmic Art
by anthropics
vendor ×10

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

15k tokens scripts
Image Enhancer
by frostant
×6

Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.

635 tokens
Video Downloader
by CommandCodeAI
×4

Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.

671 tokens
Histolab
by christophacham
×3

Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.

18k tokens
Omero Integration
by christophacham
×3

Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.

32k tokens
Pydicom
by christophacham
×3

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.

13k tokens scripts
Transformers
by christophacham
×3

This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.

13k tokens

How to use it

Copy the folder

Take gooseworks-ai/render-value-prop from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.