higgsfield-generate

Este extracto es una copia guardada durante la revisión. La fuente externa contiene la versión completa y actual.

---
version: 0.12.0
name: higgsfield-generate
description: |
  Generate images/videos/3D assets/audio via Higgsfield AI. Defaults:
  GPT Image 2 for image/design/text, Seedance 2.0 for
  video, Nano Banana 2/Lite/Pro for character/reference
  images, Marketing Studio for ads, Seed Audio 1.0 for audio.
  Use when: "generate an image", "make a video", "animate
  this photo", "image-to-video", "edit/stylize/remix this
  image", "reframe this video", "edit this video from a
  sketch", "create a 3D model/GLB", "create a sound effect",
  "make music", "text-to-audio", "create an ad", "make a UGC
  video", "unboxing", "presenter video", "import product from
  URL", or "analyze video virality". Supports generic generation,
  workflows, Marketing Studio, and Virality Predictor.
  Chain with higgsfield-soul-id for face/identity consistency.
  NOT for: Soul training, brand systems/brandbooks (use
  higgsfield-brandkit), photoshoots, cards, YouTube thumbnails
  (use higgsfield-youtube-thumbnail), explainers (use
  higgsfield-video-explainer), playable games/assets (use
  higgsfield-game-generation), or TTS.
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/3D/audio generation, 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.

Workflows are separate from models. Discover them with `higgsfield workflow list` and inspect params with `higgsfield workflow get <workflow_name>`.

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