Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add isaacsight/kernel --skill higgsfield-soul-idgit clone --depth 1 https://github.com/isaacsight/kernelWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/isaacsight/kernel/higgsfield-soul-id)<a href="https://agentmods.dev/skills/isaacsight/kernel/higgsfield-soul-id"><img src="https://agentmods.dev/badge/skills/isaacsight/kernel/higgsfield-soul-id/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/isaacsight/kernel/higgsfield-soul-id"><img src="https://agentmods.dev/badge/skills/isaacsight/kernel/higgsfield-soul-id.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00174 | $0.00896 |
| Opus 5 | $0.00087 | $0.00448 |
| Sonnet 5 | $0.00035 | $0.00179 |
| Haiku 4.5 | $0.00017 | $0.00090 |
Grade C, and why
higgsfield-soul-id scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh This is a copy
100% identical to higgsfield-soul-id — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Higgsfield Soul Character
Train a face-faithful identity model. Reusable across all Soul-powered generations.
Step 0 — Bootstrap
Before any other command:
- If
higgsfieldis not on$PATH, install it:curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh - If
higgsfield account statusfails withSession expired/Not authenticated, ask the user to runhiggsfield auth login(interactive) and wait for confirmation. - Soul training requires a paid plan (Basic+). If
higgsfield account statusshows 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 —
--imageaccepts 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.
CLI auto-uploads paths. Captures returned reference id.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> ... - Wait.
higgsfield soul-id wait <id>. Silent. Default timeout 30m. - Deliver. "Soul
<name>ready. Use in generate with--soul-id <id>."
Use the Soul
Once trained, pass to higgsfield-generate:
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
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 84 lines · 174 tokens per session scan C 1ce57e956e41
higgsfield-soul-id is a skill published in the GitHub repository isaacsight/kernel (16 stars, last pushed 10d ago), licensed MIT. It adds 174 tokens to every session and 896 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). It is 100% identical to higgsfield-soul-id, differing in 0 lines, and is treated as a copy.
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