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, Sora 2, 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 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, in-prompt first-last-frame 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 (18 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) — 11 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 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:

USER:    "Make me a cinematic chase scene through a night market.
          Use my trained Soul character — reference_id abc123."
   ↓
THIS SKILL — higgsfield-ai-prompt-skill
   • routes to higgsfield-prompt + higgsfield-camera + higgsfield-soul
   • picks Kling 3.0 (character-focused, supports --soul-id)
   • applies MCSLA: model, camera preset, subject, look, action
   • appends shared negative constraints
   • outputs a production-grade Higgsfield prompt
   ↓
PRE-FLIGHT (optional, recommended for Veo / Kling / Sora / Seedance video):

   SCHEMA VERIFY (recommended for any model you haven't called recently):
   CLI path:        higgsfield model get kling3_0
                    → returns schema: aspect_ratio enum, duration range,
                      mode/sound options, media roles
   MCP path:        models_explore(action="get", model_id="kling3_0")
                    → returns same schema as CLI

   COST ESTIMATE (no job submitted):
   MCP path:        generate_video(..., get_cost: true)
                    → returns credit cost + adjustments block

   CLI path:        higgsfield generate cost kling3_0 \
                      --prompt "<prompt from this skill>" \
                      --aspect_ratio 16:9 \
                      --duration 8
                    # (add reference flags as needed: --soul-id, --start-image,
                    #  --end-image — consult `higgsfield model get kling3_0`
                    #  for supported media roles)

   Bundled skills:  drop to CLI for the cost check (same auth, same workspace),
                    then invoke /higgsfield:generate

   Optional account checks (same data across surfaces):
   MCP path:        balance / transactions tools
   CLI path:        higgsfield account status
                    higgsfield account transactions --size 50

   Note: 2.35:1 is anamorphic STYLE vocabulary, not a valid Kling 3.0 output
         ratio. Output ratios are platform-bounded: 16:9 / 9:16 / 1:1 only.
   ↓
HIGGSFIELD STACK — one of three execution surfaces:

   CLI path:
     higgsfield generate create kling3_0 \
       --prompt "<prompt from this skill>" \
       --aspect_ratio 16:9 \
       --duration 8 \
       --wait
     # (add reference flags as needed: --soul-id, --start-image, --end-image —
     #  consult `higgsfield model get kling3_0` for supported media roles)

   Bundled skills path:
     /higgsfield:generate — takes the prompt as its --prompt argument,
     formats the CLI call above under the hood

   MCP path (claude.ai web/desktop):
     Claude invokes the Higgsfield connector with the prompt as input
   ↓
USER:    Result URL returned. Iterate if needed (this skill's
         iteration discipline applies regardless of execution surface).

The layer split holds in every case: this skill always produces the prompt, the Higgsfield stack always handles the generation call. None of the three execution paths reach back into prompt construction; this skill never shells out to their CLI or API.