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Higgsfield Soul Id

skill-moizibnyousaf-marketing-cli-higgsfield-soul-id · by MoizIbnYousaf

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Install

$ agentstack add skill-moizibnyousaf-marketing-cli-higgsfield-soul-id

Open-source listing — not yet scanned by AgentStack. Follow the source repository for install instructions.

Security review

⚠ Flagged

1 finding(s); flagged for manual review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures
  • high Pipes remote content directly into a shell (remote code execution).

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

/higgsfield-soul-id — Train a Reusable Face Identity

Train a face-faithful Soul Character model. Reusable across all Soul-powered image and video generations in higgsfield-generate.

When to use

  • User wants their face (or a specific person's face) in Higgsfield-generated images/videos
  • "train my soul", "create soul character", "make a digital twin", "brand character training"
  • Setting up a reusable identity before a campaign requiring consistent character appearance
  • The user has 5–20 photos of a face and wants them persisted as a model reference

Route elsewhere if:

  • User just wants a one-shot image with a face reference → higgsfield-generate with --image
  • User wants a fictional/non-photo avatar from a text description → higgsfield-generate with a prompt

On Activation

  1. Read brand/visual-style.md if present — check for brand character or persona notes.
  2. Ask for the name to assign to the Soul (one word, used for later reference).
  3. Ask for photos (5–20 face photos, local paths or upload UUIDs).
  4. Confirm plan tier: Soul training requires Basic+ plan. Check higgsfield account status.

Optional dependency — Higgsfield account

This skill requires the @higgsfield/cli binary and a Higgsfield account.

Without the CLI installed, return a clear actionable error:

higgsfield CLI not found. Install with:
  curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh
Then authenticate:
  higgsfield auth login

Without an authed Higgsfield account, the CLI itself surfaces the auth prompt — no special handling needed in the skill.

Fallback for image generation only: if the user just needs a one-off image and doesn't have a Higgsfield account, route them to image-gen (Gemini, model gemini-3.1-flash-image-preview, free tier). Soul Character training has no fallback — it requires Higgsfield.

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 ``

  1. If higgsfield account status fails with Session expired / Not authenticated, ask the user to run higgsfield auth login (interactive) and wait for confirmation.
  2. 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.

  1. Submit.

``bash higgsfield soul-id create --name "" --soul-2 --image ./photo1.png --image ./photo2.png ... higgsfield soul-id create --name "" --soul-2 --image --image ... `` CLI auto-uploads paths. Captures returned reference id.

  1. Wait. higgsfield soul-id wait . Silent. Default timeout 30m.
  2. Deliver. "Soul ` ready. Use in generate with --soul-id `."
  3. Log to brand assets. Append the soul reference_id to brand/assets.md so it's discoverable in future sessions without re-asking.

Use the Soul

Once trained, pass to higgsfield-generate:

higgsfield generate create text2image_soul_v2 --prompt "..." --soul-id  --wait
higgsfield generate create soul_cinema_studio --prompt "..." --soul-id  --wait

Listing existing Souls

higgsfield soul-id list                   # all references
higgsfield soul-id get                # 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 expiredhiggsfield auth login.

Anti-Patterns

| Anti-pattern | Why it fails | Instead | |---|---|---| | Submitting fewer than 5 photos | Training with too few images produces a weak identity — the soul drifts from the source face in generation. | Ask for at least 5 photos, ideally 10–15, varied angles and lighting conditions. See references/photo-guide.md. | | Using the wrong variant for the job | --soul-2 for a cinematic video generates identity but the model wasn't optimized for motion fidelity. | Pick --soul-2 for stills, --soul-cinematic for video/cinematic work. | | Not logging the referenceid | The user will need to re-ask for their soul IDs in every future session. | Always append the soul referenceid to brand/assets.md on success. | | Trying to train on free plan | Command fails mid-run with a plan error. | Check higgsfield account status before submitting. Surface the plan requirement upfront. |

Reference docs

  • references/photo-guide.md — what photos work best
  • references/troubleshooting.md — common training failures

Attribution

Ported from higgsfield-ai/skills — MIT License, Copyright (c) 2026 Higgsfield AI. Adapted for mktg's drop-in contract on 2026-05-05.

Upstream version: 0.3.0 Upstream commit: 1dcfe2687c3a9092232bac55c2b6b9ae3fc717d7

Drift detection: if the upstream skill changes, re-run mktg-steal https://github.com/higgsfield-ai/skills to evaluate the diff.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.