Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skillnpx agentmods add skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-workspacesWrote 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/osidemedia/higgsfield-ai-prompt-skill/higgsfield-workspaces)<a href="https://agentmods.dev/skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-workspaces"><img src="https://agentmods.dev/badge/skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-workspaces/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/osidemedia/higgsfield-ai-prompt-skill/higgsfield-workspaces"><img src="https://agentmods.dev/badge/skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-workspaces.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00088 | $0.04396 |
| Opus 5.5 | $0.00035 | $0.01758 |
| Sonnet 5.5 | $0.00018 | $0.00879 |
| Haiku 4.5 | $0.00009 | $0.00440 |
Grade A, and why
higgsfield-workspaces scanned grade A with 0 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 3d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- higgsfield-workspaces — 92% identical, 106 lines differ
How it starts
The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Higgsfield Workspaces — Task-First Decision Layer
Contents
- Introduction
- The Decision Matrix
- Workspace Descriptions
- The Six-Step Project Logic
- Relationship to MCSLA
- Related skills
Introduction
Higgsfield is organized around workspaces, each one tuned for a specific kind of production work. The right starting question is not "which model should I use?" but "what am I actually trying to make?" Inside a workspace, model choice still matters — it shapes quality, speed, and cost — but a workspace mismatch costs more time than a suboptimal model. Pick the workspace by the task, then pick the model by the result you want.
The Decision Matrix
| Your production problem | Start with workspace |
|---|---|
| Cinematic scene with deliberate camera direction | Cinema Studio |
| Speaking character, dubbing, or avatar video | Lipsync Studio |
| Rough idea, sketch, or storyboard test | Draw to Video / Sketch to Video |
| Fast short-form or viral-style content | Viral Hub presets (Sora 2 Trends is built on the retired Sora 2 — see its section) |
| Product ad or ecommerce variation | Click to Ad |
| Narration, voice swap, or translation | Higgsfield Audio |
If the user's task matches more than one row, pick the workspace whose output most closely resembles the final deliverable — you can always chain into another workspace for polish or audio later.
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.
- 3d ago Changed · +20 lines 32e864c395c1
- 1mo ago Changed · +29 lines · +13 tokens per session 08ecde927117
- 1mo ago First seen · 322 lines · 75 tokens per session scan A 88a43939d84e
higgsfield-workspaces is a skill published in the GitHub repository OSideMedia/higgsfield-ai-prompt-skill (800 stars, last pushed 2d ago), licensed MIT. It adds 88 tokens to every session and 4,396 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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