higgsfield-comic-to-video

higgsfield-comic-to-video is a skill for Claude Code from pixelab-ch/higgsfield-skills. It costs 132 tokens per session (1,628 once invoked), scanned A, original, MIT.

A tool workflow for turning a supplied comic panel, manga page, webtoon, or illustrated storyboard into a short video. It uses image-to-video generation, which means an existing image is required as the starting point.

In plain words
What is it for?
Use it to animate comic pages, sequential illustrations, manga, webtoons, and illustrated storyboards into videos with selected duration, resolution, and aspect ratio.
Why use it?
It provides a defined way to add motion while following the artwork’s reading order, style, and dialogue timing. Without a source image, this workflow cannot run.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to animate comic pages, sequential illustrations, manga, webtoons, and illustrated storyboards into videos with selected duration, resolution, and aspect ratio.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pixelab-ch/higgsfield-skills/04-comic-to-video
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add pixelab-ch/higgsfield-skills --skill 04-comic-to-video
Clone the repo
git clone --depth 1 https://github.com/pixelab-ch/higgsfield-skills

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for higgsfield-comic-to-video

README.md
[![agentmods](https://agentmods.dev/badge/skills/pixelab-ch/higgsfield-skills/04-comic-to-video/github.svg)](https://agentmods.dev/skills/pixelab-ch/higgsfield-skills/04-comic-to-video)
Your own site
<a href="https://agentmods.dev/skills/pixelab-ch/higgsfield-skills/04-comic-to-video"><img src="https://agentmods.dev/badge/skills/pixelab-ch/higgsfield-skills/04-comic-to-video/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for higgsfield-comic-to-video

Your own site · 80×15
<a href="https://agentmods.dev/skills/pixelab-ch/higgsfield-skills/04-comic-to-video"><img src="https://agentmods.dev/badge/skills/pixelab-ch/higgsfield-skills/04-comic-to-video.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 132 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,628 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00132 $0.01628
Opus 5.5 $0.00053 $0.00651
Sonnet 5.5 $0.00026 $0.00326
Haiku 4.5 $0.00013 $0.00163

Measured 1mo ago against content hash ef551fff52be, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

higgsfield-comic-to-video scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/04-comic-to-video/SKILL.md · 136 lines

How it starts

The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Higgsfield Comic-to-Video Skill

What this skill does

Animates a user-supplied comic panel, manga page, webtoon strip, or sequential art illustration into video. The skill reads the panel, infers narrative flow, and generates motion that respects reading order, art-style conventions, and dialogue timing.

A source image (the comic panel or page) is always required. This skill is a mandatory image-to-video (I2V) skill — it cannot run without a start image. Before any generation call can happen, the user must provide the panel file and the higgsfield:media_upload → higgsfield:media_confirm flow must complete successfully.


Model routing

Primary and fallback video models

wan2_6 (primary) seedance_2_0 (fallback)
Rationale Dedicated I2V pipeline; image role is REQUIRED Genre tone control, flexible duration, additional media roles
Quality / resolution 720p, 1080p 480p, 720p, 1080p (default 720p)
Aspect ratios 16:9, 9:16, 1:1 auto, 21:9, 16:9, 4:3, 1:1, 3:4, 9:16
Duration 5, 10, 15 s — discrete set only 4–15 s (continuous range)
Image role image x1 REQUIRED start_image or image
Genre control No Yes: auto, action, horror, comedy, noir, drama, epic

Routing rule: Use wan2_6 by default. Fall back to seedance_2_0 when: (1) wan2_6 is unavailable, (2) the user wants duration outside [5, 10, 15], (3) the user wants genre tone control, or (4) the user wants audio/end_image roles. Never switch silently — state what changes.

MODEL-06 directive: If a parameter is rejected at generation time, call higgsfield:models_explore with the target model name. Full parameter tables: references/model-specs.md.

Per-platform aspect ratio and duration

Quick rule: 9:16 for TikTok / Reels / Shorts, 16:9 for YouTube, 1:1 for Instagram feed. Full per-platform table: references/model-specs.md.

Read the full file on GitHub · 136 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 136 lines · 132 tokens per session scan A ef551fff52be

Subscribe to this mod's changes

higgsfield-comic-to-video is a skill published in the GitHub repository pixelab-ch/higgsfield-skills (10 stars, last pushed 5mo ago), licensed MIT. It adds 132 tokens to every session and 1,628 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

create-short

Create a short-form vertical video (TikTok, Instagram Reels, YouTube Shorts). Optimized 9:16 pipeline with a live Studio preview, auto-captions, hook-first structure, and background music mood selection; renders to MP4 only when you ask.

DojoCodingLabs/remotion-superpowers · 58 tokens

create-video

Full video production pipeline — from a text prompt to a live Studio preview with voiceover, music, sound effects, stock footage, and motion graphics, rendered to MP4 when you ask. The flagship command of Remotion Superpowers.

DojoCodingLabs/remotion-superpowers · 50 tokens

review-video

Review a Remotion video with AI vision. Starts with a cheap local check of rendered still frames, then has TwelveLabs watch the full render and score it against a JSON rubric (pacing, composition, text legibility, audio sync and more) with timestamped fixes, applies the fixes and re-reviews. The feedback loop that…

DojoCodingLabs/remotion-superpowers · 75 tokens

add-captions

Add TikTok-style, karaoke, YouTube or minimal captions to your Remotion video. Gets word-level captions through the official remotion-captions flow (whisper-webgpu, or ElevenLabs Scribe via @remotion/elevenlabs when there's no GPU), or imports the user's SRT with parseSrt, places one official caption element per clip…

DojoCodingLabs/remotion-superpowers · 89 tokens

analyze-footage

Analyze existing video files with TwelveLabs AI. Get a timestamped scene map of your footage, ask questions about it, find specific moments across a library, and get the best clips with timestamps for Remotion.

DojoCodingLabs/remotion-superpowers · 47 tokens

generate-clip

Generate AI video clips for your Remotion project. Create unique footage from text descriptions or animate still images into video — no stock footage needed.

DojoCodingLabs/remotion-superpowers · 32 tokens