Atlas Cloud
calesthio/OpenMontage
Generate or edit images and videos through the Atlas Cloud gateway.
A skill your agent uses whenever the user asks anything about Higgsfield AI — writing or refining video/image prompts, choosing a model (Kling, Veo, Wan, Seedance, Minimax Hailuo, DoP, Soul, Nano…
Install Higgsfield
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
Claude Code skills documentation · loads skills from .claude/skills/
Install the "higgsfield" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main into .claude/skills/higgsfield/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "higgsfield" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main into .agents/skills/higgsfield/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "higgsfield" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main into .cursor/skills/higgsfield/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "higgsfield" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main into .gemini/skills/higgsfield/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfieldInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "higgsfield" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main into .github/skills/higgsfield/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "higgsfield" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main into .opencode/skills/higgsfield/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
higgsfield- GitHub stars
- 707
- Token cost
- ~9.1k tokens
- SKILL.md length
- 4,135 words
- Files
- 199 (incl. scripts, assets)
- Skills in repo
- 33
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses whenever the user asks anything about Higgsfield AI — writing or refining video/image prompts, choosing a model (Kling, Veo, Wan, Seedance, Minimax Hailuo, DoP, Soul, Nano…
- Works in 8 steps: Routing line present. First line of… → Routed sub-skills opened and read in… → Named vocabulary verified, not invented.… → …
- The user asks anything about Higgsfield AI — writing
- SKILL.md covers HARD RULES — pre-delivery…, What Is Higgsfield?, Working Folders — file handling and Generation Ledger — log every…, plus 3 more sections
- Refining video/image prompts
What it does
Higgsfield is an agent skill from OSideMedia/higgsfield-ai-prompt-skill. Use this skill whenever the user asks anything about Higgsfield AI — writing or refining video/image prompts, choosing a model (Kling, 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"…
Its SKILL.md is about 9.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 203 other files, including scripts and assets (for example `.claude/commands/refresh-specs.md`, `.claude/commands/release.md` and `.claude/commands/validate.md`).
It sits in Media & Creative, covering AI video generation and Image generation. It works with Google Gemini, MiniMax and Seedance. The repository describes itself as: Claude AI skill for cinematic Higgsfield AI prompts — 32 sub-skills covering Seedance 2.5 (omni-reference, video edit + extend) and 2.0, the Hell Grind feature-film pipeline, an… The licence is MIT.
When your agent uses it
- The user asks anything about Higgsfield AI — writing
- Refining video/image prompts
- Choosing a model (Kling
- Camera controls
Example prompts
- “write me a video prompt”
- “make me an AI video prompt”
- “/higgsfield”
Workflow steps
8 steps, taken from the first numbered list in SKILL.md.
- Routing line present. First line of response names which sub-skills you routed to (e.g. "Routing to higgsfield-prompt + higgsfield-camera…
- 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…
- Named vocabulary verified, not invented. Camera preset names, motion preset names, model names, CLI flag forms, and MCP tool parameter…
- MCSLA structure intact on video prompts. Model · Camera · Subject · Look · Action. Five layers, every video prompt, unless the user…
- Shared negative constraints appended. Pull positive-phrasing prevention phrases from skills/shared/negative-constraints.md. Do not…
- Preflight surfaced when applicable. If execution intent is signaled (CLI / MCP / bundled-skills mentioned) AND a video-class or high-cost…
- 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…
- Prompt under 200 words — short-form regime only. Soft cap from MCSLA section. Going over is a signal you're padding rather than locking…
What it can do on your machine
Read from SKILL.md and the folder at commit 7075497. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/, which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Higgsfield loads about 9.1k tokens when it runs. Until then it costs about 147 tokens; SKILL.md has 4,135 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from OSideMedia/higgsfield-ai-prompt-skill at commit 7075497, republished under its MIT licence (© OSideMedia). 4,135 words, ~9,087 tokens.
Download SKILL.mdSave it as
.claude/skills/higgsfield/SKILL.md (or your agent's skills folder). This skill also uses 198 other files; get the full folder from GitHub.- name
- higgsfield
- description
- Use this skill whenever the user asks anything about Higgsfield AI — writing or refining video/image prompts, choosing a model (Kling, 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
- metadata.version
- 3.40.0
- metadata.updated
- 2026-09-26
- metadata.author
- O-Side Media
- metadata.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:
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.
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.mdandskills/higgsfield-prompt/SKILL.mdare mandatory at minimum on any prompt request. Grepped snippets do not satisfy this rule. Full reads do. If your only access to rootSKILL.mdorskills/higgsfield-prompt/SKILL.mdin 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.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.yamlfirst — it is generated from a datedmodels_exploresnapshot (seesnapshot_dateinside the file); if the snapshot is stale (>30 days), verify live instead (higgsfield model get <model>for CLI param schemas;models_explorefor 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.MCSLA structure intact on video prompts. Model · Camera · Subject · Look · Action. Five layers, every video prompt, unless the user explicitly opted out.
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.)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_explorefor schema, then cost estimate). Seeskills/higgsfield-stack/SKILL.md§ Preflight discipline.Aspect ratio is an enum, not a free-form value. Check the model's allowed ratios against
specs/model-specs.yamlbefore 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. Seevocab.md§ Aspect Ratio: output spec vs. style register. In a multi-shot Seedance sequence whose location plates carry a baked lens, whether the optics words still belong in the video prompt (Style Prefix included) is OPEN — one studio drops them, Hell Grind keeps the look in both (skills/higgsfield-seedance/SKILL.md§ Bake it into the asset;skills/shared/house-rulings.mdP2-6).Prompt under 200 words — short-form regime only. Soft cap from MCSLA section. Going over is a signal you're padding rather than locking — tighten. Regime exception: block-scaffold production prompts (
skills/higgsfield-seedance/SKILL.md§ Official Prompt Architecture) replace the word cap with structural lint — harvested production Seedance briefs run 218–2,059-word medians depending on register[FIELD — 13-project community harvest, 2026-07-18]. The cap governs single-shot MCSLA prompts; a block-scaffold prompt over 200 words is not a rule-8 violation.
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, Google Veo 3.1/3.1 Lite, Wan 2.7/2.6/2.5,
Seedance 2.5/2.0/Pro, FLUX 3 Video, 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 5.0 Pro/Lite/Flash + 4.5, GPT Image 2.0 / 2.5,
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. Sora 2 is retired from this skill's recommendations: OpenAI shut the Sora 2 API down on 2026-09-24; Higgsfield only ever offered it in its web UI, and whether the UI still does is unconfirmed. For scale / physics shots use Seedance 2.0 or Minimax Hailuo 2.3 (model-guide.md). Catalog check (2026-09-26): Kling 3.0 Omni, Wan 2.5, Seedance Pro, Higgsfield DoP, Soul Cinema Preview and Kling Image 3.0 / Omni are not in the API catalog (higgsfield model list / workflow list). They may be UI-only — verify in the live UI before recommending them, and prefer a catalog pick where model-guide.md names one. No catalog variant of Minimax Hailuo is named 02.
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.
| Folder | Role | Your behavior |
|---|---|---|
workspace/input/ | Documents the user wants you to read (scripts, story bibles, briefs, character sheets, references). | Read from here first. If the user uploaded a file that landed elsewhere in the project root, move it into workspace/input/ before working with it. When you need a document from the user, ask them to drop it in workspace/input/. |
workspace/output/ | Files you generate for the user (prompt packs, shot breakdowns, batch CSVs, reports, exported docs). | Write every file deliverable here, not to the project root. Tell the user the path when you finish. |
workspace/processed/ | Inputs you have finished consuming. | When a task is complete, move the source from input/ to processed/ so input/ stays clean. Never delete the user's files — relocate them. |
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.mdfirst — Fast Path means skip clarifying questions, NOT skip the file read.
| Parameter | Default |
|---|---|
| Aspect ratio | 16:9 |
| Duration | 8s (Kling lanes — see Seedance exception below) |
| Style | Cinematic |
| Video model | Kling 3.0 (character-focused) or Seedance 2.0 (action/scale/references) |
| Image model | Soul 2.0 (portrait) or Nano Banana 2 (everything else) |
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.
Seedance exception: Seedance 2.0 never gets a silently defaulted runtime (
skills/higgsfield-seedance/SKILL.md— always ask, never default). On Fast Path that means: if the user named no duration, route video to Kling 3.0; pick Seedance 2.0 only when the request names a duration — or when the user asked for Seedance by name, in which case state the assumed runtime as the first adjustable default in the delivery.
If you did not read
skills/higgsfield-prompt/SKILL.mdearlier 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: model-dependent enum — check the model's
durationvalues inspecs/model-specs.yamlbefore offering choices (e.g. Seedance 2.0 4–15s, Veo 3.1 4/6/8s; image-to-video clips trend short) - Aspect ratio: 16:9 / 9:16 / 1:1 / 4:5 / 4:3 / 21:9-where-supported (default: 16:9) — enums per model in
specs/model-specs.yaml(HARD RULE 7); anamorphic / 2.35:1 / 2.39:1 are Look-line style register, never output ratios - 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
| User wants | Route to |
|---|---|
| User unsure which workspace/tool fits, or asks "what should I use for X" | higgsfield-workspaces |
| Write or improve a prompt | higgsfield-prompt + relevant sub-skills |
| Develop a character / world / story / premise before prompting, build a character sheet / story bible, lock a visual style ("visual DNA"), keep a character consistent across many shots, or "I keep getting generic AI characters" | higgsfield-character-design |
| Audit or strengthen a scene / sequence / beat outline before generating it, or "is this scene working", "what's weak here", "why doesn't this land" | higgsfield-scene-engine |
| Cinematic still image prompt (shot framing, angles) | higgsfield-image-shots |
| GPT Image 2.0 / 2.5 / gpt-image-2 / gpt_image_2_5 prompt, Flare / Sunburst, transparent-background image, UI mockup, infographic, character/reference sheet, layout-dense image, or static-ad recreation | higgsfield-gpt-image-2 |
| Choose the right model — incl. which lane edits existing footage, which model makes one clip longer than 15s, or motion transfer (Genjutsu vs Kling Motion Control) | higgsfield-models + model-guide.md (§ Edit-Lane Chooser, § Long-Take Chooser) |
| Camera movement guidance (video) | higgsfield-camera |
| Named motion preset (Explosion, Werewolf, etc.) | higgsfield-motion |
| Visual style selection | higgsfield-style |
| Character consistency across shots | higgsfield-soul |
Consistency tie-break: character consistency via a live Soul ID / reference images inside Higgsfield → higgsfield-soul; developing WHO the character is first (sheet, story bible, visual DNA) → higgsfield-character-design. Both may apply in sequence: design first, then lock with Soul. | — |
| VFX presets (Air Bending, Plasma, etc.) | higgsfield-motion |
| One-click App workflow | higgsfield-apps |
| Genre recipe (action, horror, ad, etc.) | higgsfield-recipes |
| Fix a failing generation | higgsfield-troubleshoot |
| A Seedance take came back wrong (not flagged) — reversal, babble, a third hand, gliding walk, choppy fight | higgsfield-seedance (skills/higgsfield-seedance/FAILURE-MODES.md) + higgsfield-troubleshoot (§ Stop-Rule Ladder) |
| Moodboard, style direction, Soul Hex color | higgsfield-moodboard |
| Visual consistency across a project | higgsfield-moodboard |
| Mixed Media presets (Noir, Sketch, Particles, etc.) | higgsfield-mixed-media |
| Photodump style preset / social-feed photo-dump aesthetic | photodump-presets.md (root reference) |
| Artistic style transformation, preset stacking | higgsfield-mixed-media |
| Higgsfield Assist (GPT-5 copilot) | higgsfield-assist |
| Credit optimization, plan selection, budget strategy | higgsfield-assist |
| Cinema Studio 2.5 / Cinema Studio 3.0 / Cinema Studio 3.5 / Cinema Studio 4.0 / multi-shot sequence workflow / Soul Cast | higgsfield-cinema |
Cinema Studio 4.0 — cinematic_studio_video_4_0, its four modes (t2v / omni_reference / video_edit / video_extension), camera / lens / aperture / era / genre / pacing ids, light and palette controls | higgsfield-cinema |
| Optical physics, camera bodies, lenses, Hero Frame | higgsfield-cinema |
| Elements system (@Characters/@Locations/@Props) | higgsfield-cinema |
| Director Panel, Speed Ramp, shot modes, Popcorn | higgsfield-cinema |
| Cinema Studio 3.0 Smart mode, @ references, native audio | higgsfield-cinema |
| Cinema Studio 3.5 — three-pill UI, Style Settings, Camera Settings, Manual Style, AI director toggle | higgsfield-cinema |
User mentions Marketing Studio, DTC Ads, ms_image, or marketing_studio_video model | higgsfield-marketing-studio |
| User wants UGC / Tutorial / Unboxing / Hyper Motion / Product Review / TV Spot / Wild Card / UGC Virtual Try On / Pro Virtual Try On ad video | higgsfield-marketing-studio |
| User mentions hook+setting picklists, preset / custom / text-generated avatars in MS context, or 4–15s ad video constraints | higgsfield-marketing-studio |
| Ad Multiplier ("multiply my ad", many independently edited versions of one 4–30s ad) or a one-off Genjutsu edit of a finished ad (swap one object / product / garment using a reference image of the new one, transfer motion) | higgsfield-marketing-studio (§ 14) — a swap described in words only, with no reference image of the replacement, is Seedance 2.5 video_edit (model-guide.md § Edit-Lane Chooser) |
| User wants to run a full campaign pipeline — research → plan → generate → publish → report, "create a campaign", "100 UGC videos", content plan, batch ads, cost-savings report | higgsfield-content-factory |
| User mentions Higgsfield Canvas, a node-based / node-graph workspace, an infinite board, chaining prompts→images→videos into a pipeline, Shared Canvas, or a ComfyUI-style node workflow | higgsfield-canvas |
| Multi-shot workflow, chaining tools, full production pipeline | higgsfield-pipeline |
| Short film, branded content, Popcorn → video → assembly | higgsfield-pipeline |
| Vibe Motion, kinetic typography, animated text, infographic/data/presentation animation, logo/brand animation as code (Remotion — crisp text, exact brand colors, deployable, real-time edits) | higgsfield-vibe-motion |
| Animated AD / brand promo as an AI-generated video built brief → storyboard sheet → Seedance ("make a motion", "motion design ad", "animate my logo into a video", "promo/ad video", classicMD/highMD) | higgsfield-motion-design |
Vibe Motion vs Motion Design (both say "motion graphics / brand / logo animation"): want crisp text, exact colors, deployable code, editable canvas → higgsfield-vibe-motion (Remotion code); want a cinematic/kinetic AI video clip (pixel render, native audio, no guaranteed-crisp text) → higgsfield-motion-design (Seedance). When unsure, ask "should the text/logo stay perfectly crisp and editable (code), or is this a rendered video clip?" | — |
| Pre-generation memory check, apply past failure fixes | higgsfield-recall |
| User reports a generation result (kept/rejected/flagged) — log it to the ledger | higgsfield-recall |
| Takes-per-kept ratios, credit budgeting from logged data | higgsfield-assist |
| Audio design, dialogue cues, SFX, ambient sound | higgsfield-audio |
Standalone audio generation — soundtrack, ambience bed, multi-speaker scene audio, Seed Audio 1.0 (seed_audio), TTS voiceover / narration as its own deliverable | higgsfield-audio |
Swap or revoice the speaker in a finished video (voice_change), or clone / create a reusable voice (create_voice → voice_type: element) | higgsfield-audio |
| A finished video in, something derived out — Shorts Studio (restyle one video into shorts), Clipify (YouTube → subtitled clips), Virality Predictor ("will this go viral", score my ad), Video Analysis (scene-by-scene breakdown), and which of these cost credits | higgsfield-repurpose |
3D — image→3D / multi-view→3D / text→3D mesh (GLB), rigging or animating a mesh, remesh / retexture, 3D Body, 3D Jutsu / Scene Builder 3D projects, a 3D turnaround as a multi-angle reference, a 3D blockout as a staging reference (generate_3d, scene_builder_3d_*) | higgsfield-3d |
| Extend / continue an existing clip — "make it longer", "what happens next / before", prequel, last-frame handoff, extension chains | a native forward/backward extension on 2.5 → higgsfield-seedance-2-5 (video_extension); a 2.0 clip continued as a video reference → higgsfield-seedance (§ Extension Prompting); chaining across generations → higgsfield-pipeline (§ Continuation & Extension Handoff) |
| Prep assets / reference sheets before video — character sheet, prop three-view, location plate, "build my elements", variety sheet for crowds | templates/ad-asset-prep.md + higgsfield-gpt-image-2 (props) + higgsfield-soul (people & crowds) |
| Audition / screen-test a designed character (how they move, speak, react) before scene generation | higgsfield-character-design (§ Screen Test / Audition) |
| Seedance 2.0 / Pro prompt, flagged prompt, credit waste on Seedance | higgsfield-seedance |
| Seedance 2.5 — user names 2.5 / Dreamina / Jimeng, wants a single clip longer than 15s, wants to edit or extend a video that already exists, or supplies many image/video/audio references (up to 30/10/10) | higgsfield-seedance-2-5 |
2.0 vs 2.5 (both say "Seedance"): needs 4K, mode=fast, or a genre hint → higgsfield-seedance; needs >15s in one generation, video editing, forward/backward extension, or heavy multi-reference → higgsfield-seedance-2-5. Both do 1080p and platform start/end frames (2.5 only in omni_reference); 2.5 caps at 1080p | — |
| Character performance — acting, behavior, mannerisms, tics, a gait, subtext, "my characters look wooden / dead-eyed / AI", keeping a character themselves across many shots, an acting master profile | higgsfield-acting |
| Feature-film production pipeline on Seedance — headless character sheets, location sheets, a scene geography block reused across shots, dialogue construction, iteration discipline, giants / crowds / threshold transitions | higgsfield-seedance (HELL-GRIND.md) |
| Transform footage the user already has (video-to-video): "make a Seedance prompt for this video/clip", add a VFX element (set my head/hair on fire, transform my hand, make a limb invisible), swap the world/background around a preserved subject (desert, clouds, lava, neon city), put a giant creature behind me or on a landmark, relight/regrade to match, sync a crash-zoom/push-in to a line — a real source clip is the starting point | higgsfield-seedance-vfx |
| Replace a VFX/3D pipeline with generation — "can AI do this instead of VFX", put myself in this plate, put a creature in my footage, a dragon/monster shot without buying or rigging a 3D model, "how do I build a whole VFX shot", asset sheets → size-ref → locations → shots as one pipeline; also "my v2v keeps failing / turns to slop", scale drift between two subjects, which image model for faces vs creatures vs clothing vs locations | higgsfield-seedance-2-5 (VFX-PIPELINE.md) |
| Precise facial expression / FACS / Action Unit codes (AU12, AU6…), forced or uncanny or mixed expression, close-up micro-performance, monologue/dialogue facial acting, "which AU code for anger/fear", FACS reference sheet | higgsfield-facs |
"Make a shotlist", break a script/brief/treatment into many connected Seedance prompts, director's shotlist, global style prefix + @-glossary + named per-scene prompts as one editable HTML | higgsfield-shotlist-director |
| User has Higgsfield CLI / MCP / bundled skills installed and asks how this skill works alongside them | higgsfield-stack |
User mentions higgsfield auth login, higgsfield generate create, mcp.higgsfield.ai/mcp, /higgsfield:generate, or asks "do I need both" | higgsfield-stack |
| Request is squarely one of Higgsfield's own connector workflows (character-sheet, thumbnail-generation, ugc-*, faceless-video, narrator, subtitles, product-photoshoot, brand-asset-creation, ad-multiplier, video-editing / Higgsedit) — what this library adds vs hands off | higgsfield-stack |
| User asks where the prompt construction ends and the CLI/MCP execution begins (handoff questions) | higgsfield-stack |
Show full SKILL.md (1,355 more words)Show less
Load Map — how much to read
The routing table says where; this says how much. Loads are cumulative — every path starts from HARD RULE 2's mandatory reads.
| Situation | Load |
|---|---|
| Simple creative prompt (Fast Path) | root SKILL.md + skills/higgsfield-prompt/SKILL.md — nothing else |
| Any Seedance prompt | + skills/higgsfield-seedance/SKILL.md (+ the matching templates/seedance/ file when the request is technique-shaped) |
| Multi-scene / sequence / script breakdown | + higgsfield-shotlist-director + higgsfield-pipeline |
| Model choice unclear or contested | + higgsfield-models + specs/ (the generated spec for the output type) |
| User reports a generation result | + higgsfield-recall (ledger write) |
| A Seedance render failed (not filtered) | + skills/higgsfield-seedance/FAILURE-MODES.md + skills/higgsfield-troubleshoot/SKILL.md |
| Budget / credits / plan question | + higgsfield-assist |
| Anything else | one routing-table row → that sub-skill; resist loading more than the row names |
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.
| User request matches | Check template |
|---|---|
| Chase, pursuit, action, parkour | templates/01-cinematic-action-chase.md |
| Product, commercial, ad, UGC | templates/02-product-ugc-showcase.md |
| Horror, scary, creepy, dread | templates/03-horror-atmosphere.md |
| Fashion, editorial, lookbook | templates/04-fashion-editorial.md |
| Sci-fi, cyberpunk, VFX, space | templates/05-sci-fi-vfx.md |
| Portrait, character intro, close-up | templates/06-portrait-character-intro.md |
| Landscape, nature, establishing shot | templates/07-landscape-establishing-shot.md |
| Comedy, social media, TikTok, skit | templates/08-comedy-social-media.md |
| Romance, intimate, couple, wedding | templates/09-romantic-intimate.md |
| Dance, music, performance, concert | templates/10-dance-music-performance.md |
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:
| Technique need | Template |
|---|---|
| Pre-visualize multi-character spatial geometry before prompting | templates/seedance/top-down-map.md |
| Multi-character shot with cross-character relationships | templates/seedance/multi-character-anchor.md |
| Single-character shot with position + pose + contact-point locks | templates/seedance/single-character-position.md |
| Worked example: two-character anchoring end-to-end | templates/seedance/worked-example-two-character.md |
| Anime / stylized-2D animation — layered formula + style block + character turnaround | templates/seedance/anime-animation.md |
| Close-up facial acting via FACS Action Unit codes — beat-synced expression schedule | templates/seedance/facs-expression-beats.md |
| Seedance 2.5 multi-reference brief — role map + staged beats with end states | templates/seedance/omni-reference-2-5.md |
| Show the model WHERE figures stand — a front-on outline position reference attached LAST (one incomplete-record run: no bleed, NOT reliable at moving blocking) | templates/seedance/staging-reference.md |
Text-overlay templates (templates/text-overlays/) — paste-ready text-rendering
prompts for slogan / subtitle / speech-bubble overlays:
| Text overlay type | Template |
|---|---|
| Slogan / brand callout / opening title | templates/text-overlays/slogan.md |
| Subtitle (dialogue-synchronized) | templates/text-overlays/subtitle.md |
| Speech bubble (character-attributed) | templates/text-overlays/speech-bubble.md |
Build the Prompt Using the MCSLA Formula
Full MCSLA definition and prompt structure → skills/higgsfield-prompt/SKILL.md
Quick summary — five layers, every prompt:
| M | C | S | L | A |
|---|---|---|---|---|
| Model | Camera | Subject | Look | Action |
Core rules:
- Be specific — name camera presets, describe VFX concretely
- Keep prompts under 200 words (short-form regime — block-scaffold production prompts follow their own structural rules, HARD RULE 8)
- 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 scripts/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
| Resource | What it contains | When to use |
|---|---|---|
skills/shared/negative-constraints.md | All generation artifacts + prevention phrases, by category | Check before every prompt — append relevant constraints |
skills/shared/provenance.md | Repo-wide provenance legend — what [OFFICIAL]/[DEMO]/[FIELD]/[EMPIRICAL]/[HOUSE]/[MEASURED] mean and the evidence each requires | Before leaning on a tagged claim |
skills/shared/house-rulings.md | Every contested doctrine question — ruling or OPEN, scope, both sides | When two skill files seem to disagree |
templates/ | 10 annotated genre templates with examples, models, annotations, variations | When user request matches a common genre — use as starting point |
templates/ad-asset-prep.md | Ad asset preparation: product sheets, hero-character sheets, location plates — generate-many → test-in-motion → lock-the-winner | When an ad/product request needs reference assets built before video |
templates/character-design/ | 6 character-design worksheets (9-question sheet, story bible, visual DNA) | With higgsfield-character-design when developing characters before prompting |
templates/seedance/ | 10 Seedance technique templates: top-down-map, multi-character-anchor, single-character-position, worked-example-two-character, anime-animation, facs-expression-beats, footage-vfx-transform, global-style-prefix, omni-reference-2-5, staging-reference | When Seedance request is technique-shaped (spatial blocking, position references, multi-character anchoring, anime/stylized-2D, FACS acting, footage VFX, style prefix, 2.5 multi-reference) |
templates/text-overlays/ | 3 text-rendering templates: slogan, subtitle, speech-bubble | When user request includes on-screen text rendering |
Sub-Skills (auto-loaded as needed)
| Skill | Trigger |
|---|---|
higgsfield-workspaces | User is choosing a workspace / asking "what should I use for X" / hasn't picked a tool yet |
higgsfield-prompt | Any prompt writing or refinement request |
higgsfield-image-shots | Cinematic image prompts — shot framing, angles, composition |
higgsfield-gpt-image-2 | GPT Image 2.0 / 2.5 prompts — when to prefer 2.5 (transparent background, xhigh/max), three-format taxonomy (JSON / prose / meta-prompt), UI mockups, infographics, reference sheets, static-ad recreation |
higgsfield-models | "Which model should I use?" / model comparison / edit-lane, long-take (>15s) and motion-transfer choosers |
higgsfield-camera | Camera movement questions (video) |
higgsfield-motion | Named preset requests (Explosion, Werewolf, VFX, etc.) |
higgsfield-style | Visual style / aesthetic questions |
higgsfield-soul | Character consistency / Soul ID |
higgsfield-character-design | Pre-production story bible — premise / world / 9-question character / story spine / visual DNA (before prompting) |
higgsfield-scene-engine | Scene/sequence structural audit — Goal / Obstacle / Tactic / Reversal / Value Shift (before spending credits) |
higgsfield-apps | One-click app recommendations |
higgsfield-recipes | Genre scene templates |
higgsfield-troubleshoot | Failed generations / quality issues |
higgsfield-moodboard | Moodboard / Soul Hex / project-level style consistency |
higgsfield-mixed-media | Artistic preset overlays (Noir, Sketch, Particles, etc.) |
higgsfield-assist | Higgsfield Assist copilot / credit optimization / plan selection |
higgsfield-cinema | Cinema Studio 2.5 + 3.0 + 3.5 / Soul Cast / color grading / optical physics / multi-shot / Elements / Smart mode / @ references / Style Settings / Camera Settings / Manual Style |
higgsfield-marketing-studio | Marketing Studio / DTC Ads / ad video / UGC video / Hyper Motion / TV Spot / Wild Card / Pro Virtual Try On / hook + setting picklists / 4–15s ad video / marketing_studio_video MCP / cross-surface workflow |
higgsfield-content-factory | Campaign pipeline (research → plan → generate → publish → report) / UGC-first 5-format mix / batch generation gate / Meta Ads scheduling / cost-savings report |
higgsfield-canvas | Node-based Canvas workspace / infinite board / chain prompts→images→videos / named canvas patterns / build-free generate-paid cost model / Shared Canvas live collaboration |
higgsfield-pipeline | Multi-shot workflow / tool chaining / full production pipeline |
higgsfield-vibe-motion | Vibe Motion — motion graphics / kinetic typography / brand + logo animation as Remotion code (crisp text, exact colors, deployable) |
higgsfield-motion-design | Animated-ad flow brief → storyboard → Seedance video (AI pixel render, not code; classicMD/highMD) |
higgsfield-recall | Pre-generation memory check / apply past failure fixes |
higgsfield-audio | Audio design, dialogue, SFX, ambient sound for audio-capable models |
higgsfield-seedance | Seedance 2.0 / Pro prompt director + content-filter preflight linter (+ HELL-GRIND.md, Higgsfield's open-sourced feature-film pipeline) |
higgsfield-seedance-2-5 | Seedance 2.5 omni-reference dialect — the four modes (t2v / omni_reference / video_edit / video_extension), reference-role grammar, 30s staging, editing + forward/backward extension, keyframes, storyboards, blockouts, transitions (+ VFX-PIPELINE.md, the AI-VFX production pipeline: asset-class model routing, size-ref frame, the omni_reference v2v lane, the four-batch rule, the slop catalog) |
higgsfield-seedance-vfx | Video-to-video footage transformation for Seedance 2.0 — preserve a real subject + camera move, add a VFX element / swap the environment / drop a photoreal creature / relight to match / sync a timed zoom, run in std 4K |
higgsfield-acting | Character performance as behavior under pressure — objective / obstacle / tactics / beats / subtext, body + status + proxemics, mandatory eye life, the 150–220-word acting master profile and its per-scene rewrite, locked voice prompt |
higgsfield-shotlist-director | Brief/script → one connected Seedance shotlist (style prefix + @-glossary + named per-scene prompts) as editable HTML |
higgsfield-facs | FACS Action Unit codes for precise facial expressions in Seedance 2.0 — forced/uncanny/mixed expressions, close-up dialogue facial acting, emotion→AU recipes, FACS reference sheets |
higgsfield-stack | User mentions the Higgsfield CLI / MCP connector / bundled skills, or asks how this skill coexists with those execution surfaces |
higgsfield-3d | 3D meshes (image / multi-view / text → GLB), rigging + animation, remesh / retexture, 3D Body, 3D Jutsu scene projects, 3D turnarounds and 3D staging blockouts |
higgsfield-repurpose | Finished video in: Shorts Studio, Clipify, Virality Predictor, Video Analysis — with the paid / free split |
Full vocabulary in
vocab.mdFull motion preset library inskills/higgsfield-motion/SKILL.mdModel comparison inmodel-guide.mdExample prompts inprompt-examples.mdShared negative constraints inskills/shared/negative-constraints.mdGenre-specific annotated templates intemplates/
© OSideMedia, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 198 other files (scripts, assets) in the repository root of OSideMedia/higgsfield-ai-prompt-skill.
- SKILL.md
- .claude/commands/refresh-specs.md
- .claude/commands/release.md
- .claude/commands/validate.md
- .claude/rules/cinematic-vocab.md
- .claude/rules/image-models.md
- .claude/rules/model-reference.md
- .claude/rules/photodump-presets.md
- .claude/rules/prompt-formula.md
- .claude/settings.json
- .gitattributes
- .github/workflows/spec-drift.yml
- .github/workflows/validate.yml
- .gitignore
- .markdownlint.json
- CHANGELOG.md
- … and 183 more
Open the folder on GitHubat commit 7075497
Compare with similar skills
Higgsfield next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Higgsfield this skillOSideMedia/higgsfield-ai-prompt-skill | 707 | — | ~9.1k | Automated safety check: Pass | MIT | |
| Atlas Cloudcalesthio/OpenMontage | 66k | — | ~1.2k | Automated safety check: Pass | AGPL-3.0 | |
| Seedance Storyboard Generatorliangdabiao/Seedance2-Storyboard-Generator | 2.5k | — | ~2.2k | Automated safety check: Pass | None | |
| Imagesmixs/visual-skills | 490 | — | ~2.1k | Automated safety check: Pass | CC-BY-4.0 | |
| Nbcraftjieyefriic/nbcraft | 155 | — | ~2.8k | Automated safety check: Pass | MIT | |
| AI Video Gencalesthio/OpenMontage | 66k | — | ~3k | Automated safety check: Pass | AGPL-3.0 |
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Related
Works with
Categories
Questions about Higgsfield
What does Higgsfield do?
A skill your agent uses whenever the user asks anything about Higgsfield AI — writing or refining video/image prompts, choosing a model (Kling, Veo, Wan, Seedance, Minimax Hailuo, DoP, Soul, Nano…. Higgsfield is an agent skill from OSideMedia/higgsfield-ai-prompt-skill.ai.
When should I use Higgsfield?
Higgsfield fits situations like: the user asks anything about Higgsfield AI — writing; refining video/image prompts; choosing a model (Kling; camera controls.
How do I install Higgsfield in Claude Code?
Run `npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield -a claude-code`. Or copy the skill folder (the OSideMedia/higgsfield-ai-prompt-skill repository) into .claude/skills/higgsfield in your project. Claude Code loads it when a task matches its description.
How do I install Higgsfield in Codex?
Run `npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield -a codex`. Or copy the skill folder (the OSideMedia/higgsfield-ai-prompt-skill repository) into .agents/skills/higgsfield in your project. Codex loads it when a task matches its description.
Can I use Higgsfield in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/higgsfield, .gemini/skills/higgsfield, .github/skills/higgsfield and .opencode/skills/higgsfield in your project.
What does Higgsfield need to run?
SKILL.md names no scripts, command-line tools or credentials: Higgsfield is instructions for the agent only.
Does Higgsfield access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Higgsfield safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Higgsfield use?
Higgsfield is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Higgsfield use?
About 9.1k tokens (SKILL.md is roughly 36k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Higgsfield?
Skills that share tags, products or a category with Higgsfield: Atlas Cloud (calesthio/OpenMontage, 66k stars), Seedance Storyboard Generator (liangdabiao/Seedance2-Storyboard-Generator, 2.5k stars), Image (smixs/visual-skills, 490 stars) and Nbcraft (jieyefriic/nbcraft, 155 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Higgsfield?
OSideMedia (a GitHub user) maintains it in OSideMedia/higgsfield-ai-prompt-skill, which has 707 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on September 27, 2026.
Source: OSideMedia/higgsfield-ai-prompt-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.