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no-more-higgsfield

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- manifest.md
- models.md
- static-formats.md
- variation-dimensions.md
- gallery.py
- generate.py
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ad-creative-engine.skill
README.md
SKILL.md

# Use via CDN

jsDelivr

jsDelivr serves any public GitHub repository as a CDN with zero setup. Pick a version and a file to get a ready-to-paste link and snippet.

Version

File

Link

Example

Command Glossary

Commands referenced in this DOCs, explained below.

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`git clone`

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Clone an existing repository.

git clone {{remote_repository_location}} {{path/to/directory}}

Clone an existing repository into a new directory (the default directory is the repository name):

git clone --recursive {{remote_repository_location}}

Clone an existing repository and its submodules:

git clone {{[-n|--no-checkout]}} {{remote_repository_location}}

Clone only the `.git` directory of an existing repository:

🔍

`python3`

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This command is an alias of `python`.

tldr python

View documentation for the original command:

// repository documentation

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by Mike Futia — https://www.skool.com/scale-ai/about

A [Claude Code](https://claude.com/claude-code) skill that replaces subscription AI creative tools (Higgsfield, Krea, Freepik AI) with pay-per-asset generation through a single [fal.ai](https://fal.ai) API key.

Drop in a winning Meta static ad and get back a complete testing matrix: copy variations (different hooks, angles, CTAs), new static ad images via GPT Image 2, and the winners animated into video via Kling or Seedance — all grounded in your brand's actual guidelines, voice, and customer language.

**A 5-variation testing cycle costs about $0.35. Animating a winner adds ~$0.50. Slow months cost $0.**

## Why this beats a subscription

- **Pay for output, not capacity.** No $49–$99/month whether you generate or not.
- **It reads your brand.** Approved claims, banned words, your customer's exact language — every generation is grounded in your brand files. No subscription tool can do this.
- **Cost quoted before anything fires.** Every run shows a per-asset cost table first, and a hard budget cap is enforced in code — the script refuses to submit anything over budget.
- **You own everything.** Every asset downloads to your disk immediately, every prompt and cost is logged, and a local gallery shows your whole library. No deletion windows, no content-rights fine print.

## Install

**Claude desktop app** (recommended): download [`ad-creative-engine.skill`](./ad-creative-engine.skill) from this repo, then in the app go to **Customize → Skills → Upload skill** and select the file. Done.

**Claude Code CLI**: clone straight into your skills folder:

```bash
git clone https://github.com/mikefutia/no-more-higgsfield.git ~/.claude/skills/ad-creative-engine
```

**Both paths** then need the Python environment (one-time — or just ask Claude: *"set up the ad-creative-engine skill's Python environment"* and it'll run this for you):

```bash
python3 -m venv ~/.config/ad-creative-engine/venv
~/.config/ad-creative-engine/venv/bin/pip install fal-client python-dotenv requests
```

Finally, get a fal.ai key (fal.ai → Settings → API Keys), load $10 of pay-as-you-go credit, and save it:

```bash
mkdir -p ~/.config/fal && echo 'FAL_KEY=your-key-here' > ~/.config/fal/.env && chmod 600 ~/.config/fal/.env
```

(A `.env` file in your project folder or an exported `FAL_KEY` env var also works.)

## Use

In a project folder, set up your brand context once — Claude drafts it for you:

```
Draft my three brand foundation files from https://yourbrand.com — brand/brand-dna.md
(products, approved claims, visual identity, what we can NEVER say in Meta ads),
brand/brand-voice.md (tone, do/don't words), and brand/icp-cards.md (target customer,
pain points, voice-of-customer phrases, objections).
```

Review the drafts — every future ad inherits them. Then drop your winning ad image into the folder and run the matrix:

```
Use the ad-creative-engine skill. My winning static ad is reference-ad.png and my brand
files are in brand/. Generate 5 ad variations spanning at least
3 different ad formats — each with a different hook angle, plus full Meta ad copy for each. Keep the total under $3 and
show me the cost quote before you generate anything.
```

Pick your winners, then:

```
Use the ad-creative-engine skill. Animate variation-3.png into a 5-second ad video with
Kling — slow push-in, subtle atmosphere. Quote me the cost first.
```

And to browse everything you've ever generated:

```
Rebuild my generations gallery and open it.
```

## What's in the box

| File | What it does |
|---|---|
| `SKILL.md` | The skill itself — workflow, hard rules, model routing |
| `scripts/generate.py` | fal.ai runner: parallel jobs, budget enforcement, local downloads, JSONL logging |
| `scripts/gallery.py` | Builds a local, self-contained HTML gallery from the generation log |
| `references/variation-dimensions.md` | The variation framework: 8 hook angles, length/CTA/register rules, image treatments, anti-patterns |
| `references/static-formats.md` | 12 static ad formats (testimonial, comparison chart, billboard, benefit stack…) with GPT Image 2 briefing notes |
| `references/models.md` | Model catalog with endpoints and verified prices (GPT Image 2, Nano Banana, Kling, Seedance, FLUX…) |
| `references/manifest.md` | Job manifest format for the runner |

## Guardrails baked in

1. Cost table shown **before** any generation
2. Hard budget cap enforced in code (default $3/session) — over-budget manifests refuse to submit
3. Batch brake: >12 jobs or >$5 in one run requires explicit confirmation
4. Every output saved locally immediately; every prompt, cost, and seed logged to `generations/log.jsonl`
5. Never generates ad copy without your brand foundation files

## Notes

- Prices drift. The skill verifies a model's current fal.ai price on first use and updates its own price table.
- Supplement/health brands: the brand-dna template includes Meta compliance restrictions (no second-person health states, no outcome promises). Always run your own policy check before launching.

---

Built with Claude Code. From the [SCALE AI](https://www.skool.com/scale-ai/about) community.