higgsfield-generate

Dieser Auszug wurde bei der Prüfung gespeichert. Die externe Quelle enthält die vollständige und aktuelle Version.

---
version: 0.3.0
name: higgsfield-generate
description: |
  Generate images/videos via Higgsfield AI. Default: GPT
  Image 2 for images/design/text, Seedance 2.0 for video,
  Nano Banana 2/Pro for character/reference image work,
  Marketing Studio for ads with avatars/products/hooks,
  settings, plus Soul V2/Cinema/Cast/Location and Kling
  3.0. Use when: "generate an image", "make a video",
  "animate this photo", "image-to-video",
  "edit/stylize/remix this image", "produce a clip",
  "create an ad", "make a UGC video", "product demo",
  "unboxing", "brand video", "presenter video",
  "import product from URL", "create avatar for ad",
  or "analyze video virality". Supports image-to-image,
  image-to-video, references, job/upload IDs, and
  Marketing Studio. Chain with higgsfield-soul-id for
  face/identity consistency. Virality Predictor
  (`brain_activity`) analyzes video virality: hook strength,
  attention, retention, distraction risk, and creative
  score. NOT for: Soul Character training (use
  higgsfield-soul-id), product photoshoots, marketplace
  listing cards, text/chat/TTS tasks.
argument-hint: "[prompt-or-analysis-request] [--model <name>] [--image|--video <path-or-id>]"
allowed-tools: Bash
---

# Higgsfield Generate

Submit jobs to any Higgsfield model. Wraps the `higgsfield` CLI. Covers generic image/video gen, Marketing Studio (branded ads, avatars, products, hooks, settings), and, secondarily, Virality Predictor video scoring.

## Step 0 — Bootstrap

Before any other command:

1. If `higgsfield` is not on `$PATH`, install it:
   ```bash
   curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh
   ```
2. If `higgsfield account status` fails with `Session expired` / `Not authenticated`, ask the user to run `higgsfield auth login` (interactive) and wait for confirmation.


## UX Rules

1. Be concise. No raw IDs, no JSON dumps in chat. Print the media URL for generated assets, or the text summary for Virality Predictor.
2. No internal jargon. Don't narrate "calling higgsfield cost", "polling job".
3. Detect the user's language from the first message and reply in it. Technical args (`--aspect_ratio 16:9`) stay English.
4. Don't batch-ask. Pick a sane default model and ask one thing at a time only if genuinely missing.
5. Don't pre-estimate cost or optimize for cheaper models unless the user asks. Prefer the quality default first.
6. Pass `--wait` to `generate create` so the command blocks until done and prints the result URL itself. Avoid the two-step `create` → `wait` pattern.

## Discovery guardrail

When looking for a Higgsfield feature/model, do not rely only on semantic search or CLI `--help`. First run an unfiltered model list, then inspect likely `job_set_type` names. If the user says a model exists but search returns no results, trust that signal and verify with the full model list before answering.

Virality Predictor is exposed as:

- Customer-facing name: Virality Predictor
- Technical `job_set_type`: `brain_activity`
- Category/output: text report. This is video-in/text-out analysis, not a text/chat generation model.
- Input: uploaded video
- Purpose: finished-video hook, attention, retention, and virality analysis

If the user says "analyze this video", "score this ad", "evaluate the hook", or similar, route to `brain_activity` even though it appears under text/analysis models. Classify by task intent and required input, not by output category alone.

## Workflow — generic generation

1. **Pick a model.** Start with the core defaults unless the brief clearly needs a specialist:

   - **GPT Image 2** → default image model for high-fidelity general generation, graphic design, UI, banners, typography, and on-image text.
   - **Seedance 2.0** → default video model for serious motion, cinematic clips, multi-shot work, image-to-video, and 4–15s production-quality output. 12s is valid.
   - **Nano Banana 2/Pro** → default for character, cartoon, stylized, and reference-driven i