higgsfield-ai-prompt-skill

Higgsfield AI Prompt Skill

A comprehensive Claude skill library for generating high-quality prompts on Higgsfield AI — the cinematic video and image generation platform.

What This Skill Does

Transforms natural language requests into production-ready Higgsfield prompts using:

• The MCSLA formula (Model · Camera · Subject · Look · Action)
• Named camera controls and motion presets the platform recognizes
• Model selection guidance across Kling 3.0 / 3.0 Omni / 3.0 Motion Control, Veo 3.1, Wan, Seedance 2.5 / 2.0, FLUX 3 Video, Minimax Hailuo, Higgsfield DoP, and more
• Genre recipe templates for action, horror, romance, sci-fi, product ads, and more
• Soul ID character consistency guidance + Character Sheet creation
• Troubleshooting for failed or poor generations
• Cinema Studio 2.5 advanced features: Soul Cast AI actors, built-in color grading, 3D Mode (Gaussian Splatting), Grid Generation, Resolution Settings, Frame Extraction Loop, Object & Person Insertion, Per-Character Emotions, Clustering, Five-View Location Reference Sheet, Reference Sheet Types (Motion / Outfit / Palette), Elements System with library surface (5 source tabs × 6 element categories)
• Cinema Studio 3.0 (Business/Team plan): native dual-channel stereo audio, Smart shot control, 15s max duration, 7 genres, @ reference patterns, Soul Cast 3.0
• Cinema Studio 4.0 (cinematic_studio_video_4_0, CLI workflow): the Seedance 2.5 four-mode surface (t2v / omni_reference / video_edit / video_extension) plus camera body / lens / aperture / era / genre / pacing and light / palette controls — schema-documented, not yet field-rated
• 3D (higgsfield-3d): image / multi-view / text → GLB meshes, rigging + a 678-clip animation library, remesh / retexture, 3D Jutsu scene projects, 3D turnarounds and staging blockouts
• Repurposing (higgsfield-repurpose): Shorts Studio, Clipify, Virality Predictor, Video Analysis — with the paid / free split
• Cinema Studio 3.5: three-pill main UI (Genre / Style / Camera), Style Settings panel (8 Color Palette / 6 Lighting / 9 Camera Moveset Style + Manual Style mode), Camera Settings four-axis panel (3 Camera Body / 5 Lens / 5 Focal Length including new 75mm / 3 Aperture), Image Mode with four Cinematic models picker (Soul Cinema default, Cinematic Characters, Cinematic Locations, Cinematic Cameras with 2.5 vocabulary)
• Seedance 2.0 prompting best practices — Intent over Precision, Genre Router, I2V Gate, Anti-Slop, Physics Language, SCELA audio, Reference-Based / Continuation / Expand Shot / Edit Shot / Transformation prompt modes, Continuation Prompt Formula, the Iteration Rule
• Seedance 2.5 omni-reference director — the four generation modes (t2v / omni_reference / video_edit / video_extension), explicit @Image / @Video / @Audio reference roles with exclusions, the five-step multi-reference workflow, 30-second staging with end states, timestamp pacing, bracket syntax for music / SFX / dialogue / subtitles, first-last-frame control (platform start_image/end_image in omni_reference, or declared in-prompt) and multi-keyframe control, storyboard grids, coarse-vs-fine blockout rendering, one-click video, seamless transitions, and a 2.0-vs-2.5 routing table
• Hell Grind feature-film pipeline — Higgsfield's open-sourced 95-minute-feature system: headless character sheets, mask-composited point edits, location sheets with anchors and one light logic, the per-scene GEO SPATIAL LAYOUT block, the position-fixing first second, dialogue construction, the ban dictionary, the 10–15 iteration rule, and the crowd / giant / threshold solutions
• AI-VFX pipeline — the production layer under Seedance 2.5, from Higgsfield's AI-vs-VFX challenge build: model routing per asset class (faces / creatures / clothing / locations), the plain-grey sheet law, two-close-up creature sheets, the face-lock crop, the size-ref frame for scale between two subjects, location batching selected on light, the omni_reference video-to-video lane (source ≥4s, duration = source) with its performance-inheritance clause, the four-batch stop rule and the i2v fallback with a deliberate empty-frame stitch point, and a slop catalog of the tells that give a shot away
• Acting director — performance as behavior under pressure: objective / obstacle / tactics / beats / subtext, listening markers, body + status + proxemics, mandatory eye life, the 150–220-word acting master profile and its per-scene rewrite, the locked voice prompt, a 15-symptom atlas of bad acting, and a 0–5 performance scale
• GPT Image 2.0 prompt director — three-format taxonomy (structured JSON for UI mockups / infographics / reference sheets, dense cinematic prose for single-subject scenes, auto-derive meta-prompt for theme-only concepts) plus reference-sheet and static-ad-recreation workflow satellites
• Higgsfield Canvas — node-based / infinite-board workspace guidance: chaining prompts → images → videos, named canvas patterns, Shared Canvas live collaboration, build-free / generate-paid cost model
• Marketing Studio + Content Factory — 9 DTC ad presets (UGC / Tutorial / Unboxing / Hyper Motion / TV Spot / Wild Card / Virtual Try-On) with 4–15s ad video, plus an end-to-end campaign pipeline (research → plan → generate → publish → report) with a cost-savings report
• Shared negative constraints reference — categorized artifacts + prevention phrases (positive alternatives for 3.0); Kling 3.0 Motion Control failure diagnostic; Physics Rendering — Resolution Decision Matrix (cross-model 480p / 720p / 1080p routing rule for Seedance 2.0 + Cinema Studio 3.x)
• Identity vs. Motion separation — hard rule for character consistency across shots
• Annotated templates library — 10 genre templates with Cinema Studio 3.0 genre mappings, plus Seedance technique + character-design + text-overlay sub-libraries (19 files across 3 categories)
• DISCIPLINE.md cross-cutting framework — 9 named discipline patterns in 3-3-3 tier symmetry (prompt-construction, model-selection, iteration-discipline) governing decisions across all sub-skills
• production-benchmarks.md — Hell Grind 90-min Cannes feature reference, per-character iteration anchors, acceptance-rate calibration; what "production quality" means in practice
• FAILURE-MODES.md (Seedance) — 15 named render failures documented with symptom + mechanism + counter for diagnosis-first iteration
• C-arc Building Complete AI Projects — 10-Step Methodology — end-to-end pipeline from idea to delivered project; complements the genre/scene templates
• Expanded Seedance methodology + Soul refinement — Iteration Rule + 6-Pass Diagnostic Sequence + Four Questions + Next-Shot Decision Tree + Bridging / Continuation / Repair working modes; Character Anchor Block + Two-Tool Refinement Pipeline for character consistency at production scale

Install

Claude Code

git clone https://github.com/OSideMedia/higgsfield-ai-prompt-skill ~/.claude/skills/higgsfield

Claude Code registers the root SKILL.md as one skill, higgsfield. The 35 sub-skills under skills/ are not registered separately; the root routes to each by its full path and Claude opens it from there. The skill's scripts need only python3 (standard library).

Your documents and the skill's deliverables go in a workspace/ folder (input/, output/, processed/) inside the project you are working in, created on first use. Your documents and deliverables are never written into ~/.claude/skills/higgsfield/, so updating or reinstalling the skill never touches them. The learning memory and generation ledger live in ~/.higgsfield-skill/db/, outside the skill folder, so an update or reinstall keeps them too. The skill creates that folder on first use from its own db/, which also carries over the memory from an install older than v3.42.0. If you had two older installs (say a personal one and one inside a project), the second one's own entries are kept in ~/.higgsfield-skill/unmerged/, not merged into the first; where lists them. In Cowork, or when you run the skill from a clone of this repo, the memory stays in the skill's own db/. To see which folder is in use, run python3 scripts/higgsfield_memory.py where from the skill's folder.

Claude Cowork

Drop the repo folder into your Cowork workspace. The skill dispatcher is at SKILL.md in the repo root.

Claude.ai Projects

Upload SKILL.md (root) as your project instruction base. Upload files from skills/ as project documents.

Higgsfield Stack Integration

This skill is the prompt-construction layer. Higgsfield ships official execution tooling — a CLI, an MCP custom connector, and a bundled skills package. They complement each other: this skill produces the prompt, their tooling executes it. None of their tooling is required for this skill to work — you can always paste prompts directly into higgsfield.ai. But if you want an end-to-end loop, you'll want one of the three.

A Higgsfield account is required for any of the tooling below. Sign up at higgsfield.ai.

Higgsfield CLI

Command-line tool for terminal-native agents (Claude Code, Codex, Cursor). Per Higgsfield's own guidance, prefer the CLI over the MCP if you're working in a terminal.

• Repo: github.com/higgsfield-ai/cli
• Install: curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh or brew install higgsfield-ai/tap/higgsfield
• Auth: higgsfield auth login

Higgsfield MCP

Custom connector for claude.ai web and the Claude desktop app. Separate product from the CLI.

• Connector URL: https://mcp.higgsfield.ai/mcp
• Install: claude.ai → Settings → Connectors → Add custom connector → paste the URL above → sign in

Higgsfield Bundled Skills

Markdown skill bundle for agents that consume Cowork-style skills. All three skills drive the CLI under the hood.

• Repo: github.com/higgsfield-ai/skills
• Install: npx skills add higgsfield-ai/skills
• Skills included: higgsfield-generate, higgsfield-soul, higgsfield-product-photoshoot
• Invoke: /higgsfield:generate, /higgsfield:soul, /higgsfield:product-photoshoot

End-to-end example

How the layers fit together for a real request: