Higgsfield Models
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user asks which model to use, wants to compare models, or needs guidance on selecting between Kling, Wan (incl.
Draft and refine prompts for video generation models (including text-to-video, image/keyframe-to-video, and reference-driven generation), and create character-sheet prompts for image models when the…
$ npx skills add Square-Zero-Labs/video-prompting-skill --skill video-prompting -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Square-Zero-Labs/video-prompting-skill video-prompting --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/Square-Zero-Labs/video-prompting-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/video-prompting .claude/skills/video-prompting && 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 "video-prompting" agent skill from https://github.com/Square-Zero-Labs/video-prompting-skill/tree/main/video-prompting into .claude/skills/video-prompting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-prompting", 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/Square-Zero-Labs/video-prompting-skill/tree/main/video-promptingType 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 Square-Zero-Labs/video-prompting-skill --skill video-prompting -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Square-Zero-Labs/video-prompting-skill video-prompting --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Square-Zero-Labs/video-prompting-skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/video-prompting .agents/skills/video-prompting && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "video-prompting" agent skill from https://github.com/Square-Zero-Labs/video-prompting-skill/tree/main/video-prompting into .agents/skills/video-prompting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-prompting", 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 Square-Zero-Labs/video-prompting-skill --skill video-prompting -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Square-Zero-Labs/video-prompting-skill video-prompting --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Square-Zero-Labs/video-prompting-skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/video-prompting .cursor/skills/video-prompting && 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 "video-prompting" agent skill from https://github.com/Square-Zero-Labs/video-prompting-skill/tree/main/video-prompting into .cursor/skills/video-prompting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-prompting", 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/Square-Zero-Labs/video-prompting-skill.git --path video-prompting--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 Square-Zero-Labs/video-prompting-skill --skill video-prompting -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Square-Zero-Labs/video-prompting-skill video-prompting --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Square-Zero-Labs/video-prompting-skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/video-prompting .gemini/skills/video-prompting && 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 "video-prompting" agent skill from https://github.com/Square-Zero-Labs/video-prompting-skill/tree/main/video-prompting into .gemini/skills/video-prompting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-prompting", 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 Square-Zero-Labs/video-prompting-skill video-promptingInstalls 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 Square-Zero-Labs/video-prompting-skill --skill video-prompting -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Square-Zero-Labs/video-prompting-skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/video-prompting .github/skills/video-prompting && 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 "video-prompting" agent skill from https://github.com/Square-Zero-Labs/video-prompting-skill/tree/main/video-prompting into .github/skills/video-prompting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-prompting", 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 Square-Zero-Labs/video-prompting-skill --skill video-prompting -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Square-Zero-Labs/video-prompting-skill video-prompting --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Square-Zero-Labs/video-prompting-skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/video-prompting .opencode/skills/video-prompting && 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 "video-prompting" agent skill from https://github.com/Square-Zero-Labs/video-prompting-skill/tree/main/video-prompting into .opencode/skills/video-prompting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-prompting", 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.
video-promptingDraft and refine prompts for video generation models (including text-to-video, image/keyframe-to-video, and reference-driven generation), and create character-sheet prompts for image models when the…
Video Prompting is an agent skill from Square-Zero-Labs/video-prompting-skill. Draft and refine prompts for video generation models (including text-to-video, image/keyframe-to-video, and reference-driven generation), and create character-sheet prompts for image models when the goal is character consistency before image-to-video. Use when a user asks for a "video prompt", a model-specific prompt such as MiniMax H3, Seedance 2.0, Seedance 2.5, Ovi, Veo 3, Wan 2.2, Wan Animate 2, LTX-2, LTX-2.3, or LTX-2.5, or a consistent-character prompt such as "character sheet prompt", "character…
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 36 other files, including reference files (for example `references/models/ltx2-3/prompting.md`, `references/models/ltx2-5/prompting.md` and `references/models/ltx2/example_prompts/ltx2_examples.md`).
It sits in Media & Creative, covering AI video generation. It works with Seedance, MiniMax and Google Veo. The repository describes itself as: AI Agent Skill for Prompting Video Models. The licence is Apache-2.0.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 8d72999. 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.
Video Prompting loads about 1.9k tokens when it runs, and up to ~51k if it reads all its reference files. Until then it costs about 150 tokens; SKILL.md has 964 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 Square-Zero-Labs/video-prompting-skill at commit 8d72999, republished under its Apache-2.0 licence (© Square-Zero-Labs). 964 words, ~1,936 tokens.
.claude/skills/video-prompting/SKILL.md (or your agent's skills folder). This skill also uses 26 other files; get the full folder from GitHub.Turn a user’s intent into either:
Model-specific video guidance lives in references/models/. Character-sheet guidance lives in references/workflows/character-sheets.md.
This file is the entry point: route to the right path, ask the minimum clarifying questions, then draft the prompt in the expected format.
references/models/ovi/prompting.mdreferences/models/veo3/prompting.mdreferences/models/wan22/prompting.mdreferences/models/wan-animate-2/prompting.mdreferences/models/seedance2/prompting.mdreferences/models/seedance2-5/prompting.mdreferences/models/minimax-h3/prompting.mdreferences/models/ltx2/prompting.mdreferences/models/ltx2-3/prompting.mdreferences/models/ltx2-5/prompting.mdreferences/workflows/character-sheets.mdTo add a new model later: create references/models/<model>/prompting.md, then add it to this index.
To add a new workflow later: create references/workflows/<workflow>.md, then add it to the Workflow Index.
These rules apply to every video model reference:
Decide whether the user wants:
Route to the character-sheet workflow when the user wants a reusable reference sheet, turnaround, expression sheet, costume sheet, photographic identity sheet, or a consistent-character starting point for a longer image-to-video project.
If the user is asking for both, do them in this order:
If the user did not name a model, ask which model they are using (or offer supported options from the Model Index).
Then confirm the input mode. Start with text-to-video (t2v) or image-to-video (i2v), and use any additional keyframe or full-reference modes supported by the selected model guide.
For MiniMax H3, distinguish T2VA, I2VA, first-and-last-frame-to-video (FL2VA), last-frame-to-video (L2VA), and full-reference mode. Ask for the effective duration when a final-frame alignment or timed cuts require it.
For Seedance 2.5, distinguish text-to-video, image-to-video, reference-to-video, edit, and extend. Ask for the effective duration when a multi-beat timeline is needed, and ask for the intended ending state on long or continuity-sensitive shots. Recommend the shortest duration that fits the action instead of defaulting every request to the model's maximum.
If i2v: ask the user to share the image (optional, but it will help you generate a better prompt). Use the image as an anchor according to the chosen model’s guidance (e.g., keep identity/wardrobe/composition stable; focus your text on motion/camera/what changes).
If the chosen model has versions, duration constraints, or required parameters, ask the minimum questions needed to select the right format (see the model guide). For LTX-2.3 specifically: default to 10 seconds as the external duration setting when duration is missing, ask if the user wants shorter or longer, and scale motion complexity to match that duration. Do not write the duration into the prompt itself.
For LTX-2.5 specifically: distinguish a continuous single shot from a native multi-shot scene, screenplay-style dialogue, Dub-It speech replacement, and Video Editing IC-LoRA. When the user asks for settings, no fixed length is required, and the interface supports it, recommend automatic duration as an external setting. Use a fixed external duration when last-frame conditioning is supplied. Do not write duration or setting names into the prompt itself.
For video prompts: open the model’s prompting.md from the Model Index and follow its rules strictly.
For character sheets: open references/workflows/character-sheets.md and follow its structure strictly. Treat this as an image-model prompt, not a video-model prompt.
Draft the prompt using the structure and constraints from the markdown file you selected in Step 3.
For video prompts: follow the chosen model’s prompting.md exactly, including its preferred section order, dialogue/audio format, and any shot-structure guidance.
Before returning a video prompt, remove any prompt-internal references to model name/version, clip length, aspect ratio, resolution, or generation settings except timing required by the selected model's prompt schema.
For character sheets: follow references/workflows/character-sheets.md exactly, including layout, consistency constraints, and expression-row guidance.
Default: output only the final prompt text. Default formatting: output prompts as a single line with no line breaks unless the user explicitly requests multiline formatting or the selected model guide requires a structured multiline schema. MiniMax H3 is such an exception: preserve its required field names, line order, and blank-line separation. Seedance 2.5 is another exception for complex timed or reference-driven shots: preserve the guide's production-note sections and timeline line breaks. For LTX-2.5, preserve multiline screenplay formatting when dialogue or beat clarity benefits from it; keep single-shot, image-to-video, and multi-shot prose as one paragraph by default.
If the user asks for options: provide 2–3 distinct prompt variants, each fully self-contained and compliant with the model’s formatting.
If the model uses required API parameters (e.g., duration/size), include a short “Recommended parameters” line only when the user has specified them or explicitly asks for them.
If the user wants the full consistency workflow, after the character-sheet prompt also provide:
© Square-Zero-Labs, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 26 other files (references) in video-prompting of Square-Zero-Labs/video-prompting-skill.
Open the folder on GitHubat commit 8d72999
Video Prompting 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 |
|---|---|---|---|---|---|---|
| Video Prompting this skillSquare-Zero-Labs/video-prompting-skill | 182 | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Higgsfield ModelsOSideMedia/higgsfield-ai-prompt-skill | 707 | — | ~7k | Automated safety check: Pass | MIT | |
| Video Audio Continuitynodetool-ai/nodetool | 560 | — | ~1.2k | Automated safety check: Pass | AGPL-3.0 | |
| HiggsfieldOSideMedia/higgsfield-ai-prompt-skill | 707 | — | ~9.1k | Automated safety check: Pass | MIT | |
| VideoNexus-JPF/note-companion | 870 | 3 repos | ~3.6k | Automated safety check: Pass | MIT | |
| AI Video Gencalesthio/OpenMontage | 66k | — | ~3k | Automated safety check: Pass | AGPL-3.0 |
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user asks which model to use, wants to compare models, or needs guidance on selecting between Kling, Wan (incl.
nodetool-ai/nodetool
Keep sound continuous across a multi-scene piece cut from generated video — why one clip per scene hard-cuts the audio at every boundary, when to write all the scenes into a single generation…
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…
Nexus-JPF/note-companion
When the user wants to create, generate, or produce video content using AI tools or programmatic frameworks.
calesthio/OpenMontage
Generate AI videos from text prompts using multiple provider gateways.
Hao0321/ai-media-generator
為使用者產生高品質的 AI 生圖、生影片、生音樂提示詞,並在需要時透過瀏覽器自動化實際送到目標平台。涵蓋 OiiOii、Kling 3.0/O-series、Seedance 2.0/2.5、Suno v5.5、Seedream 5.0/4.0、Vidu Q3、Midjourney V8.1、Flux 1.1 Pro / Kontext、Runway Gen-4.5 /…
Works with
Categories
Draft and refine prompts for video generation models (including text-to-video, image/keyframe-to-video, and reference-driven generation), and create character-sheet prompts for image models when the…. Video Prompting is an agent skill from Square-Zero-Labs/video-prompting-skill. Draft and refine prompts for video generation models (including text-to-video, image/keyframe-to-video, and reference-driven generation), and create character-sheet prompts for image models when the goal is character consistency before image-to-video.
Video Prompting fits situations like: A user asks for a video prompt; A model-specific prompt such as MiniMax H3; A consistent-character prompt such as character sheet prompt; character turnaround.
Run `npx skills add Square-Zero-Labs/video-prompting-skill --skill video-prompting -a claude-code`. Or copy the skill folder (video-prompting in Square-Zero-Labs/video-prompting-skill) into .claude/skills/video-prompting in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Square-Zero-Labs/video-prompting-skill --skill video-prompting -a codex`. Or copy the skill folder (video-prompting in Square-Zero-Labs/video-prompting-skill) into .agents/skills/video-prompting 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 Square-Zero-Labs/video-prompting-skill --skill video-prompting -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/video-prompting, .gemini/skills/video-prompting, .github/skills/video-prompting and .opencode/skills/video-prompting in your project.
SKILL.md names no scripts, command-line tools or credentials: Video Prompting 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.
Video Prompting is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.9k tokens (SKILL.md is roughly 7.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 49k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Video Prompting: Higgsfield Models (OSideMedia/higgsfield-ai-prompt-skill, 707 stars), Video Audio Continuity (nodetool-ai/nodetool, 560 stars), Higgsfield (OSideMedia/higgsfield-ai-prompt-skill, 707 stars) and Video (Nexus-JPF/note-companion, 870 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Square-Zero-Labs (a GitHub user) maintains it in Square-Zero-Labs/video-prompting-skill, which has 182 GitHub stars. The repository was last updated on August 25, 2026.
Source: Square-Zero-Labs/video-prompting-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.