higgsfield

name: higgsfield description: > Use this skill whenever the user asks anything about Higgsfield AI — writing or refining video/image prompts, choosing a model (Kling, Sora 2, Veo, Wan, Seedance, Minimax Hailuo, DoP, Soul, Nano Banana, Seedream, Flux, GPT Image, etc.), camera controls, named motion presets, Soul ID character consistency, Cinema Studio 2.5/3.0, Vibe Motion, troubleshooting failed generations, credit optimization, Photodump, or any mention of higgsfield.ai. Also trigger on generic "write me a video prompt" or "make me an AI video prompt" requests when Higgsfield is the user's configured platform. user-invocable: true metadata: tags: [higgsfield, video, image, prompt, cinematic, AI, filmmaking, motion, camera] version: 3.15.2 updated: 2026-06-22 author: O-Side Media license: MIT

Higgsfield AI Prompt Skill

Language rule: Reply in whatever language the user writes in.

HARD RULES — pre-delivery checklist

These rules apply to every Higgsfield response. They are written as a pre-delivery checklist the agent runs before sending the response, not as prohibitions stated and then forgotten. The failure mode they prevent is plausibility-over-verification — producing a response that looks correct because the agent's training data knows the rough shape of Higgsfield work, rather than because the agent actually read the skill files and verified the platform's ground truth.

Before delivering any Higgsfield response, confirm in this order:

1. Routing line present. First line of response names which sub-skills you routed to (e.g. "Routing to higgsfield-prompt + higgsfield-camera for an Atmosphere push-in"). One line, then the work. Missing routing line = response is incomplete; add it.

2. Routed sub-skills opened and read in this conversation. Match the user's ask to the routing table below, open the matching sub-skill files with the read tool, and READ them. Root SKILL.md and skills/higgsfield-prompt/SKILL.md are mandatory at minimum on any prompt request. Grepped snippets do not satisfy this rule. Full reads do. If your only access to root SKILL.md or skills/higgsfield-prompt/SKILL.md in this conversation came from grep results, you have not satisfied this rule — open the file. Platform vocabulary, preset names, and model parameters must come from the files because this platform's lineup changes between releases.

3. Named vocabulary verified, not invented. Camera preset names, motion preset names, model names, CLI flag forms, and MCP tool parameter names all come from the skill files or from verification. For model parameters, enums, and durations, verify against specs/model-specs.yaml first — it is generated from a dated models_explore snapshot (see snapshot_date inside the file); if the snapshot is stale (>30 days), verify live instead (higgsfield model get <model> for CLI param schemas; models_explore for MCP). If you found yourself thinking "this flag probably looks like X" or "this preset is probably called Y" — stop. Read the file or run the verification command. Plausibility is not validity. Do not substitute generic video-prompt vocabulary for named Higgsfield presets; do not invent model versions, camera presets, or motion-preset names. If the user names one you don't see in the skill files, say so and ask for clarification.

4. MCSLA structure intact on video prompts. Model · Camera · Subject · Look · Action. Five layers, every video prompt, unless the user explicitly opted out.

5. Shared negative constraints appended. Pull positive-phrasing prevention phrases from skills/shared/negative-constraints.md. Do not paraphrase from training; use the exact phrasing from the file. (Kling 3.0 prefers positive phrasing over negations; using negation-form constraints when the file says positive is a fidelity miss.)

6. Preflight surfaced when applicable. If execution intent is signaled (CLI / MCP / bundled-skills mentioned) AND a video-class or high-cost model is named OR a budget concern is named, surface the two-step preflight (model get / models_explore for schema, then cost estimate). See skills/higgsfield-stack/SKILL.md § Preflight discipline.

7. Aspect ratio is an enum, not a free-form value. Check the model's allowed ratios against specs/model-specs.yaml before writing them into the header; if the snapshot is stale (>30 days), verify live via schema (models_explore / model get). Example of why this matters: Seedance 2.0 supports native 21:9, Kling 3.0 does not. Anamorphic / 2.35:1 / 2.39:1 are style register vocabulary for the Look line, not output ratios. See vocab.md § Aspect Ratio: output spec vs. style register.

8. Prompt under 200 words. Soft cap from MCSLA section. Going over is a signal you're padding rather than locking — tighten.

If any of items 1–8 are missing or unverified, the response is incomplete. Complete them before sending, not after.

What Is Higgsfield?

Higgsfield is a cinematic AI video and image generation platform built for filmmakers and creators. Unlike single-model tools, Higgsfield hosts multiple generation engines on one platform — Kling 3.0/3.0 Omni/3.0 Motion Control, Sora 2, Google Veo 3.1/3.1 Lite, Wan 2.7/2.6/2.5, Seedance 2.0/Pro, Minimax Hailuo 2.3/02, Higgsfield DoP (Lite/Standard/Turbo) for video; Soul 2.0, Soul Cinema Preview, Soul Cast, Nano Banana Pro/2, Kling Image 3.0/Omni, Seedream 4.0, GPT Image 2.0, Flux 2/Kontext for images — plus a library of 100+ named Motion Presets, a Soul ID character consistency system, Cinema Studio 2.5, Cinema Studio 3.0 (Business/Team plan), and Cinema Studio 3.5 with Soul Cast AI actors, native dual-channel stereo audio, and 80+ one-click Apps.

Working Folders — file handling

The project has a workspace/ folder with three subfolders. Use them for every task that involves a user-provided document or a file you produce. This keeps uploads and deliverables out of the project root.

Rules:

• Never scatter user uploads or generated files across the project root or skill folders — route them through workspace/.
• Treat workspace/input/ as the canonical place to look when the user says "the script / bible / reference I gave you."
• These three folders' contents are local-only (git-ignored); do not assume anything in them is committed.

Fast Path — Simple Creative Requests

If the user provides a clear creative intent ("write me a prompt for a car chase at night") with no specific constraints, generate immediately using these sensible defaults:

Fast Path still requires reading skills/higgsfield-prompt/SKILL.md first — Fast Path means skip clarifying questions, NOT skip the file read.

Do not ask clarifying questions. Deliver a ready-to-paste prompt. Mention the defaults used so the user can adjust if they want something different.

If you did not read skills/higgsfield-prompt/SKILL.md earlier in this conversation, read it now before writing the prompt.

Full Path — Production Requests

When the user signals production-grade intent (Cinema Studio, multi-shot, specific model, budget constraints, client work), confirm before generating:

Required:

• Generation type: Image / Video / App (one-click)
• Video duration: 5s / 10s (image-to-video clips are 3–5s; text-to-video up to 10s+)
• Aspect ratio: 16:9 / 9:16 / 1:1 / 4:5 / 4:3 / 2.35:1 (default: 16:9)
• Model preference (or ask Claude to recommend — see skills/higgsfield-models/SKILL.md)

Optional (skip if user already provided):

• Visual style: Cinematic / VHS / Super 8MM / Anamorphic / Abstract
• Soul ID character reference (if character consistency needed)
• Reference image for image-to-video
• Motion preset preference

Ask everything in one message — do not split across multiple rounds.

Route to the Right Skill

Check Templates for Genre Match

Before writing a prompt from scratch, check if the user's request matches a common genre pattern. The templates/ folder contains 10 annotated example templates with line-by-line breakdowns, recommended models, negative constraints, and variations.

Use the template as a starting point — adapt the example prompt to the user's specific request. The annotations explain WHY each element works, helping you make informed substitutions.

Technique templates (templates/seedance/) — structure templates for Seedance prompts where the user request is technique-shaped rather than genre-shaped:

Text-overlay templates (templates/text-overlays/) — paste-ready text-rendering prompts for slogan / subtitle / speech-bubble overlays:

Build the Prompt Using the MCSLA Formula

Full MCSLA definition and prompt structure → skills/higgsfield-prompt/SKILL.md

Quick summary — five layers, every prompt:

Core rules:

• Be specific — name camera presets, describe VFX concretely
• Keep prompts under 200 words
• Subject → Action → Camera → Style is the most reliable order

Output Format

Single prompt:

**Model**: [model name]
**Aspect ratio**: [ratio]  **Duration**: [Xs]  **Style**: [style]

[Prompt]

**Camera**: [camera control name]
**Motion preset** (if used): [preset name]

Two versions (when style varies):

### Version 1 — [Style Name]
[Prompt]

---
### Version 2 — [Style Name]
[Prompt]

Output rules:

• Output a clean, ready-to-paste prompt — no meta-commentary after
• Do not explain what every line does unless the user asks
• Always name the camera control and motion preset explicitly

Generation Ledger — log every result

Every generation attempt the user reports — kept, rejected, or filter-flagged — gets one row in db/ledger/<project>.json. The denominator (successes too, not just failures) is what turns the memory system into takes-per-kept ratios and credit budgets.

The 5-second rule: when the user reports a result, ask at most ONE question ("keep or reject — what failed?") and write the row yourself with one higgsfield_memory.py log-gen command. Never ask twice; never present a form. Full workflow: skills/higgsfield-recall/SKILL.md § Log the Generation Result. Ratios and budgeting: skills/higgsfield-assist/SKILL.md.

@ Reference Rules

• User uploads a document (script, bible, brief, reference notes): read it from workspace/input/; if it landed elsewhere, move it there first (see Working Folders above)
• User uploads image: use [reference image] or describe it as "the provided reference"
• For Soul ID character: note "using Soul ID character reference" in the prompt
• For video extension: note "extend from [reference video], continue with..."
• For style transfer: note "match the visual style of [reference image]"

Shared Resources

Sub-Skills (auto-loaded as needed)

Full vocabulary in vocab.md Full motion preset library in skills/higgsfield-motion/SKILL.md Model comparison in model-guide.md Example prompts in prompt-examples.md Shared negative constraints in skills/shared/negative-constraints.md Genre-specific annotated templates in templates/