Scroll Promo Site Builder
kangarooking/kangarooking-skills
Create a scroll-controlled cinematic product website with rich motion (动效网站) from product materials, reference pages or videos, and brand assets.
Tests whether a scene is structurally worth generating before any shot is prompted — a five-element engine of Goal, Obstacle, Tactic, Reversal, and Value Shift.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-scene-engine -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield-scene-engine --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/higgsfield-scene-engine .claude/skills/higgsfield-scene-engine && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "higgsfield-scene-engine" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-scene-engine into .claude/skills/higgsfield-scene-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-scene-engine", 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.
$skill-installer install https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-scene-engineType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-scene-engine -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield-scene-engine --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/higgsfield-scene-engine .agents/skills/higgsfield-scene-engine && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "higgsfield-scene-engine" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-scene-engine into .agents/skills/higgsfield-scene-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-scene-engine", 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-scene-engine -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield-scene-engine --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/higgsfield-scene-engine .cursor/skills/higgsfield-scene-engine && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "higgsfield-scene-engine" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-scene-engine into .cursor/skills/higgsfield-scene-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-scene-engine", 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.
$ gemini skills install https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git --path skills/higgsfield-scene-engine--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-scene-engine -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield-scene-engine --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/higgsfield-scene-engine .gemini/skills/higgsfield-scene-engine && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "higgsfield-scene-engine" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-scene-engine into .gemini/skills/higgsfield-scene-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-scene-engine", 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 higgsfield-scene-engineInstalls 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-scene-engine -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/higgsfield-scene-engine .github/skills/higgsfield-scene-engine && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "higgsfield-scene-engine" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-scene-engine into .github/skills/higgsfield-scene-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-scene-engine", 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-scene-engine -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-scene-engine --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/higgsfield-scene-engine .opencode/skills/higgsfield-scene-engine && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "higgsfield-scene-engine" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-scene-engine into .opencode/skills/higgsfield-scene-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-scene-engine", 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.
higgsfield-scene-engineTests whether a scene is structurally worth generating before any shot is prompted — a five-element engine of Goal, Obstacle, Tactic, Reversal, and Value Shift.
Higgsfield Scene Engine is an agent skill from OSideMedia/higgsfield-ai-prompt-skill. Tests whether a scene is structurally worth generating before any shot is prompted — a five-element engine of Goal, Obstacle, Tactic, Reversal, and Value Shift. Use when the user has a scene, sequence, beat outline, or script and wants it audited or strengthened; when a sequence generates cleanly but lands flat and nobody can say why; when shots look good individually but the run of them does not build; or when the user asks 'is this scene working', 'what's weak here', or 'why doesn't this land'. Upstream of…
Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Media & Creative, covering Comics and storyboards and AI video generation. 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.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 7075497. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Higgsfield Scene Engine loads about 2.8k tokens when it runs. Until then it costs about 188 tokens; SKILL.md has 1,443 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.
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); files beside SKILL.md are not scanned.
The full file from OSideMedia/higgsfield-ai-prompt-skill at commit 7075497, republished under its MIT licence (© OSideMedia). 1,443 words, ~2,800 tokens.
.claude/skills/higgsfield-scene-engine/SKILL.md (or your agent's skills folder).[EMPIRICAL — Tigran's tig-scene-engine skill (2026-06-26), re-derived 2026-08-22] These definitions are
bespoke and deliberately not the textbook ones. Apply them as written; do not substitute
standard screenwriting glosses, which are looser and will pass scenes this engine fails.
Why a prompter carries this. Every shot costs credits and iterations. A structurally dead scene generates just as cleanly as a live one — the model has no opinion about whether a beat earns its place — so the failure surfaces only after the footage exists and the cut does not build. This skill is the cheapest pass in the repo: it runs on text, before any generation, and its whole job is to stop you paying to render a scene that cannot work.
It decides which shots deserve the spend. higgsfield-shotlist-director turns the
settled scene into shots; higgsfield-acting writes the performance inside them.
The single, unchanging thing the hero is fighting for: to fix what has already been established and reach, as fast as possible, the result that resolves it. "Already established" means anything set up earlier — deep backstory, a few scenes ago, or one minute ago.
A strong circumstance that jeopardizes either one stage of the path or the whole goal. It threatens; it does not merely cost.
The move the threat forces the hero to choose — a reasonable guess on his current, often incomplete, knowledge. This is search under uncertainty, not error-as-stupidity.
A turn against expectation. Three forms:
Placement: at least one reversal per sequence. A single scene may be pure escalation, but a resolved sequence with zero reversals fails.
A sequence is the run of scenes from when a specific jeopardy opens to when it resolves — overcome, or it defeats him and forces a new path. Sequences nest, and each resolving unit needs its own reversal. Flag which scale you are auditing.
The change in the AUDIENCE'S read of a character, triggered by a reversal. The keystone, and the most misunderstood element: it does not happen on the page, it happens in the viewer's mind. Each reversal forces the audience to re-judge the character — a moving verdict they keep revising (nice → experienced → cunning → no, he's desperate → devoted son → what a man).
THE CORE RULE: a reversal with no value shift is inert. A structural turn is not a reversal unless it moves the audience's verdict. If you cannot name a before-verdict and an after-verdict the audience would hold, the turn is dead weight no matter how much plot flipped.
Audit the trajectory, not just presence: are the revaluations building a deepening portrait, or just oscillating?
Goal (fixed; every scene a causal link toward it) → Obstacle (jeopardizes a stage or the whole goal; name what is at risk + scale) → Tactic (forced by the threat; a reasonable guess; its outcome must return information) → Reversal (turn against expectation; ≥1 per resolved sequence) → Value Shift (the audience re-judges the character; no shift → the reversal is useless)
Work the chain in order. Reversal and Value Shift are judged at the sequence level, not the scene.
SCENE/SEQUENCE: <one-line identification>
CHAIN CHECK
• Goal — <verdict + one line>
• Obstacle — <what's jeopardized + scale + verdict>
• Tactic — <forced? reasonable? returns info? verdict>
• Reversal — <form + present? ≥1 in sequence? verdict>
• Value Shift — <before-verdict → after-verdict per reversal, or INERT; trajectory note>
WEAKEST POINT: <the single element that, if fixed, recovers the most>
WHAT IF…
1. (Minimal) <change ONLY the weakest point so the rest of their scene still works>
2. (Clean) <a version that fully works, even if it departs further from the original>
3. (Optional) <only if it genuinely adds something>The three tiers matter in that order: minimal preserves the user's version, clean is yours, and the third is optional. Do not collapse them into one rewrite.
Once the chain holds, the scene is worth spending on — and only then:
| Next | Skill |
|---|---|
| Who these people are, and their bible | ../higgsfield-character-design/SKILL.md |
| The shared scene direction and each character's fuel | ../higgsfield-acting/SKILL.md § The layer above the pillars |
| Breaking the settled scene into shots | ../higgsfield-shotlist-director/SKILL.md |
| Writing the shot itself | ../higgsfield-seedance/SKILL.md · ../higgsfield-seedance-2-5/SKILL.md |
The most common real failure to hunt for first: a reversal that turns the plot but does not move the audience's verdict. Surface it before anything else — it is the one that survives a read-through, generates beautifully, and still lands flat in the cut.
higgsfield-actingThis engine and ../higgsfield-acting/SKILL.md § The five pillars share three words and
define them differently, on purpose: this file audits structure (does the scene earn its
credits), acting writes playable behaviour (what the body does in the shot). Carry an
audit result into acting through this map, not by assuming the words mean the same thing
(../shared/house-rulings.md P3-5):
| Here (structure) | In acting (performance) | How one feeds the other |
|---|---|---|
| Goal — the hero's single unchanging story goal; each scene goal a causal link toward it | Super-objective (story-wide) and objective — what one character wants in this scene, from a specific person, as a verb aimed at the partner | The scene goal names the step; acting turns it into a partner-directed verb for each character, including the ones this audit never mentions |
| Obstacle — a circumstance that jeopardizes a stage or the whole goal; name what is at risk and its scale | Obstacle and stakes — what prevents the want, external or internal (pride, disbelief), plus the cost of failure | The audited jeopardy becomes the stakes; acting adds the internal obstacles a structural audit does not look for |
| Tactic — the plot-level move the threat forces, a reasonable guess under uncertainty whose failure must return information | Tactics — moment-to-moment action verbs toward the partner (press · charm · stall), changed when one fails | One structural tactic is usually played as several acting tactics; a structural wheel-spin shows up in acting as monotactics |
| Reversal and Value Shift — judged at the sequence level, in the audience's verdict | Beats — each visible change of tactic; subtext | A value shift needs a visible beat change to land on screen; if acting cannot point to the beat, the shift will not render |
../higgsfield-character-design/SKILL.md — premise, world, character, story bible../higgsfield-acting/SKILL.md — the performance layer inside a settled scene../higgsfield-shotlist-director/SKILL.md — scene → shot list© OSideMedia, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/higgsfield-scene-engine of OSideMedia/higgsfield-ai-prompt-skill.
Open the folder on GitHubat commit 7075497
Higgsfield Scene Engine 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 Scene Engine this skillOSideMedia/higgsfield-ai-prompt-skill | 707 | — | ~2.8k | Automated safety check: Pass | MIT | |
| Scroll Promo Site Builderkangarooking/kangarooking-skills | 661 | — | ~2.6k | Automated safety check: Pass | MIT | |
| Motion Graphics Music Videomakevoid/motion-graphics-music-video-skill | 141 | — | ~3.3k | Automated safety check: Pass | MIT | |
| Music VideoNoizAI/skills | 526 | — | ~1.5k | Automated safety check: Pass | None | |
| Video ComposeUtopai-Research/pai-code | 355 | — | ~4.1k | Automated safety check: Pass | Custom licence | |
| Xianxia Cinematic Video Directorliyue-aigc/xianxia-cinematic-video-director | 269 | — | ~1.4k | Automated safety check: Pass | None |
kangarooking/kangarooking-skills
Create a scroll-controlled cinematic product website with rich motion (动效网站) from product materials, reference pages or videos, and brand assets.
makevoid/motion-graphics-music-video-skill
Create and revise animated character music videos from a supplied song and creative prompt, with researched storyboards, Fal character and video generation, p5 motion graphics, audio editing, and…
NoizAI/skills
Build a music video from an existing song and lyrics, either as p5.js/p5.brush animation or by assembling local images and clips.
Utopai-Research/pai-code
Generates and prompts video clips on the filmmaking canvas. An agent skill from Utopai-Research/pai-code.
liyue-aigc/xianxia-cinematic-video-director
Design, derive, optimize, explain, and diagnose cinematic Eastern xianxia camera direction, storyboards, motion choreography, pacing, continuity locks, keyframes, and per-shot image-to-video prompts.
elementsix/elementsix-skills
Interviews you about a video idea, then writes a timed shot-by-shot prompt for Seedance 2.0 using its image, video and audio reference syntax.
OSideMedia/higgsfield-ai-prompt-skill
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…
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user asks about Higgsfield Assist (the built-in GPT-5 copilot), how to use the platform's native AI assistant, credit optimization strategies, plan selection, how to…
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user wants to generate a cinematic still image on Higgsfield, asks about shot framing, camera angle, or composition for image prompts, needs a specific shot type…
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user asks about Mixed Media, wants to apply artistic preset styles to an image (Noir, Sketch, Paper, Canvas, Particles, Neon, etc.), combine multiple artistic…
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user asks about Moodboard, building a moodboard from reference images, curated moodboard presets, Soul Hex color transfer, applying a visual style direction to…
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user wants to apply a named Higgsfield motion preset, asks about VFX presets, transformation effects, elemental effects, or transition presets.
Categories
Tests whether a scene is structurally worth generating before any shot is prompted — a five-element engine of Goal, Obstacle, Tactic, Reversal, and Value Shift. Higgsfield Scene Engine is an agent skill from OSideMedia/higgsfield-ai-prompt-skill. Tests whether a scene is structurally worth generating before any shot is prompted — a five-element engine of Goal, Obstacle, Tactic, Reversal, and Value Shift.
Higgsfield Scene Engine fits situations like: the user has a scene; script and wants it audited; A sequence generates cleanly but lands flat and nobody can say why; shots look good individually but the run of them does not build.
Run `npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-scene-engine -a claude-code`. Or copy the skill folder (skills/higgsfield-scene-engine in OSideMedia/higgsfield-ai-prompt-skill) into .claude/skills/higgsfield-scene-engine in your project. Claude Code loads it when a task matches its description.
Run `npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-scene-engine -a codex`. Or copy the skill folder (skills/higgsfield-scene-engine in OSideMedia/higgsfield-ai-prompt-skill) into .agents/skills/higgsfield-scene-engine in your project. Codex loads it when a task matches its description.
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-scene-engine -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-scene-engine, .gemini/skills/higgsfield-scene-engine, .github/skills/higgsfield-scene-engine and .opencode/skills/higgsfield-scene-engine in your project.
SKILL.md names no scripts, command-line tools or credentials: Higgsfield Scene Engine is instructions for the agent only.
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.
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. Review the folder before installing.
Higgsfield Scene Engine is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Higgsfield Scene Engine: Scroll Promo Site Builder (kangarooking/kangarooking-skills, 661 stars), Motion Graphics Music Video (makevoid/motion-graphics-music-video-skill, 141 stars), Music Video (NoizAI/skills, 526 stars) and Video Compose (Utopai-Research/pai-code, 355 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
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.