Skill detail

higgsfield-soul-id

Official Higgsfield workflow for training reusable face-identity models.

MatchDirectReviewed for higgsfield
Sourcehiggsfield-ai/skillsExternal source
Reported installs103,344Popularity signal only

Inspect before use

Automated review checks relevance, not safety or endorsement. Read the source instructions before using this skill.

Saved source preview

SKILL.md

The saved excerpt is a snapshot from review. The external source remains the complete and most current version.

---
version: 0.12.0
name: higgsfield-soul-id
description: |
  Train a Soul Character — a personalized model on a person's face that
  Higgsfield uses for identity-faithful image and video generation.
  Use when: "create my Soul", "train my face", "make my digital twin",
  "build me an avatar", "learn my appearance", "create a character of me",
  "set up identity for video", "I want my face in generated images".
  Chain: train Soul (one-time, returns reference_id) → use in
  higgsfield-generate via `--soul-id <id>` with models like
  `text2image_soul_v2` or `soul_cinema_studio`.
  NOT for: one-shot face swaps (use higgsfield-generate with --image),
  named-character / non-photo avatars (use higgsfield-generate with prompt).
argument-hint: "[name] [photo paths...]"
allowed-tools: Bash
---

# Higgsfield Soul Character

Train a face-faithful identity model. Reusable across all Soul-powered generations.

## 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.
3. Soul training requires a paid plan (Basic+). If `higgsfield account status` shows free plan, tell the user before submitting.

## UX Rules

1. Be concise. No raw IDs in chat. Just say "Soul ready" with a name reference.
2. Detect language and respond in it. CLI flags stay English.
3. Ask for the smallest set of inputs: name + photos. Pick a sensible model variant.
4. Polling is silent — training takes minutes. Don't repeat status updates.

## Workflow

1. **Get name.** One word, used for later reference. Ask if missing.
2. **Get photos.** 5–20 face photos, varied angles and lighting. Local paths or already-uploaded IDs both work — `--image` accepts either.
3. **Pick variant.**
   - `--soul-2` — for image generation (default)
   - `--soul-cinematic` — for cinematic / video work
   Choose based on user's stated downstream use. Default to `--soul-2`.
4. **Submit.**
   ```bash
   higgsfield soul-id create --name "<name>" --soul-2 --image ./photo1.png --image ./photo2.png ...
   higgsfield soul-id create --name "<name>" --soul-2 --image <upload_id> --image <upload_id> ...
   ```
   CLI auto-uploads paths. Captures returned reference id.
5. **Wait.** `higgsfield soul-id wait <id>`. Silent. Default timeout 30m.
6. **Deliver.** "Soul `<name>` ready. Use in generate with `--soul-id <id>`."

## Use the Soul

Once trained, pass to `higgsfield-generate`:

```bash
higgsfield generate create text2image_soul_v2 --prompt "..." --soul-id <ref_id> --quality 2k --wait
higgsfield generate create soul_cinematic --prompt "..." --soul-id <ref_id> --quality 2k --wait
```

## Listing existing Souls

```bash
higgsfield soul-id list                   # all references
higgsfield soul-id get <id>               # one by id
```

## Errors

- `Minimum Basic plan required` — user is on free plan; tell them.
- `Training failed` — check photos quality (5+ unique faces, well-lit).
- `Session expired` → `higgsfield auth login`.

## Reference docs

- `references/photo-guide.md` — what photos work best
- `references/troubleshooting.md` — common training failures
Read the full source on GitHub (opens external page)
Context

Related work