Render Brand Identity Reveal logo

Render Brand Identity Reveal

OrganizationPopular
gooseworks-ai
render-brand-identity-reveal

Render a 'brand identity reveal' video from a config — a single poster frame in a real, softly-lit space (real wall, soft-focus plant in the corner, dappled leaf shadow, illuminated poster) whose artwork HARD-CUTS through ~10 on-brand poster mockups (hero product, IG post, hanging banners, sticker sheet, logo lockup, poster, two lifestyle stills, packaging, big icon) then holds on a brand end card. The environment plate is one create-image-fal generation; the mockups are real-DOM HTML frame-stepped via Playwright, perspective-composited into the detected frame quad with the plate's real leaf-shadow multiplied back onto each poster (reads as behind glass), sequenced by FFmpeg. Deterministic assembly, FREE (the plate comes from create-image-fal, the bed from create-music-elevenlabs), music bed only and approved brand copy only. Use for the brand-identity-reveal format.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill namerender-brand-identity-reveal
Stars
1.2K
Forks
208
Bundled files
10
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.

  • 10 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 Brand Identity Reveal 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.
  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/render-brand-identity-reveal .claude/skills/render-brand-identity-reveal
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Render Brand Identity Reveal 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 Brand Identity Reveal 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 Brand Identity Reveal 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-brand-identity-reveal

Render the 'brand identity reveal' format from a config. The signature is a single fixed poster frame in a REAL, softly-lit space (the illuminated poster-frame look of a boutique/cinema): a real wall, a real soft-focus plant in the lower-left corner, dappled leaf shadow. The artwork INSIDE the frame HARD-CUTS (no crossfade) through 11 beats — 10 on-brand poster mockups + a brand END CARD held ~3s. Music bed only, NO voiceover; copy is baked into each mockup, never overlaid as captions.

This capability is the FREE assembly only. The paid parts are separate generic capabilities the recipe names — create-image-fal (the one-shot environment plate) and create-music-elevenlabs (the bed). Never re-implement them here.

Three layers

  1. Environment plate (PAID, create-image-fal, flux-pro ultra, 9:16) — an empty lit poster frame in a real space, high-res so the camera can be pushed closer by cropping. Pick a wall color that makes the brand's poster colors POP (complement of the dominant hue).
  2. Mockups (FREE) — real-DOM HTML/CSS (scene.html), one poster per beat, built from the brand's real assets + approved copy, frame-stepped via Playwright (render_art.py, bare mode, device_scale_factor 2).
  3. Composite (FREE) — measure_frame.py detects the blank poster interior quad; composite.py perspective-warps each poster into it AND multiplies the plate's real leaf-shadow/light back onto the poster (so it reads as behind glass) + a glass sheen; build_video.sh sequences the frames with the music bed.

Inputs

  • config.json — copy scripts/config.example.json and edit (canvas, plate prompt + wall_style, camera crop, per-beat durations, end-card copy). Schema + per-file working-dir layout are documented in scripts/PIPELINE.md.
  • The brand's REAL product/packaging/lifestyle stills, wordmark, and icon (recreate the icon as an SVG <mask> if the only source has an occluding element). Approved copy only.

Workflow (free assembly)

bash
CAP=skills/ads/capabilities/render-brand-identity-reveal
RUN=<project>/working    # holds scene.html + assets/ + the create-image-fal plate in bg/

python3 $CAP/scripts/recrop.py 0.72 0.13      # camera distance (bigger frac = bigger frame)
python3 $CAP/scripts/measure_frame.py         # detect the blank poster interior quad
python3 $CAP/scripts/render_art.py            # render each poster standalone (Playwright, dsf 2)
python3 $CAP/scripts/composite.py             # warp into frame + shadow multiply + sheen
bash    $CAP/scripts/build_video.sh $RUN/concat.txt $RUN/music.mp3 out.mp4 13.05 1.0

Then watch the master (music-only, every poster legible, shadow falls across the art, end card holds). See scripts/PIPELINE.md for adapting scene.html per brand.

Rules

  • Approved brand copy ONLY — never invent claims, customers, results, or testimonials.
  • Toggle beats with OPACITY, not display (a per-state display:flex silently overrides a display:none toggle and paints one state over all others).
  • Camera distance = re-crop the high-res plate (recrop.py), don't regenerate.
  • The realism trick = MULTIPLY the plate's real shadow/light back onto each composited poster.
  • Music bed only, no VO. Close on the brand end card.

Failure Modes

  • Every rendered frame identical → a per-beat display: rule beat the visibility toggle; use opacity.
  • Playwright evaluate(fn, arg) didn't switch state in a loop → bake the beat index into the JS string and return the applied state to assert it.
  • Composited poster looks pasted-on → you skipped the shadow multiply (shadow_strength ~0.85).
  • Studio product won't cut out (white cap == seamless bg) → present as a photo-tile, don't corner-flood-fill.
  • Playwright missing under node → use the python playwright + cached chromium.

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 Brand Identity Reveal AI skill do?

Render a 'brand identity reveal' video from a config — a single poster frame in a real, softly-lit space (real wall, soft-focus plant in the corner, dappled leaf shadow, illuminated poster) whose artwork HARD-CUTS through ~10 on-brand poster mockups (hero product, IG post, hanging banners, sticker sheet, logo lockup, poster, two lifestyle stills, packaging, big icon) then holds on a brand end card. The environment plate is one create-image-fal generation; the mockups are real-DOM HTML frame-stepped via Playwright, perspective-composited into the detected frame quad with the plate's real lea...

Why use Render Brand Identity Reveal on TypingMind?

Because you install it once and use it with any model. Render Brand Identity Reveal 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 Brand Identity Reveal 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-brand-identity-reveal. 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 Brand Identity Reveal?

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 Brand Identity Reveal?

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

Is the Render Brand Identity Reveal 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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