video-generation

Instructions for generating videos from structured prompts, with optional reference images. Prompts can describe scenes, camera movement, dialogue, and audio.

In plain words
What is it for?
Creating videos, animations, or clips; specifying visual scenes and sound; and using an image as a reference or as the first or last frame.
Why use it?
It provides a defined workflow for turning a video idea into a generated clip and for guiding the result with an existing image.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/comisai/comis/video-generation
Any agent
npx skills add comisai/comis --skill video-generation
Clone the repo
git clone --depth 1 https://github.com/comisai/comis

Made for: Claude Code, Codex.

Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 878 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00066 $0.00878
Opus 5 $0.00033 $0.00439
Sonnet 5 $0.00013 $0.00176
Haiku 4.5 $0.00007 $0.00088

Measured 2d ago against content hash 35bd064a7d3c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

video-generation 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 2d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/generate.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

packages/daemon/bundled-skills/video-generation/SKILL.md · 100 lines

How it starts

The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Video Generation

Generate high-quality videos using structured JSON prompts and a bundled Python script. Supports a reference image as guidance or as the first/last frame.

All script paths below are relative to this skill's directory. Resolve them against the directory containing the manifest file shown in <location> (e.g., if <location> is ~/.comis/skills/video-generation/SKILL.md, then scripts/generate.py means ~/.comis/skills/video-generation/scripts/generate.py). Invoke the resolved script by its absolute path while keeping the tool working directory inside the execution workspace. Never set cwd to the skill directory; it is outside workspace bounds. In command examples below, replace each relative scripts/... path with its resolved absolute path.

Write prompt files and generated outputs to your workspace directory (shown in the "Workspace" section of your system prompt).

The bundled script requires the requests Python package (pip install requests).

Workflow

Step 1: Understand requirements

Identify from the user's request:

  • Subject/content: What should be in the video
  • Style preferences: Art style, mood, color palette
  • Technical specs: Aspect ratio, composition, lighting
  • Reference image: Any image to guide generation

Step 2: Create structured prompt

Write a JSON prompt file to your workspace directory with naming pattern {descriptive-name}.json.

Step 3: Create reference image (optional)

If the image-generation skill is available, generate a reference image first. A single reference image is used as the guided frame of the video.

Step 4: Execute generation

python3 scripts/generate.py \
  --prompt-file ~/.comis/workspace/prompt-file.json \
  --output-file ~/.comis/workspace/generated-video.mp4 \
  --aspect-ratio 16:9

With reference image:

python3 scripts/generate.py \
  --prompt-file ~/.comis/workspace/prompt-file.json \
  --reference-images /path/to/ref.jpg \
  --output-file ~/.comis/workspace/generated-video.mp4 \
  --aspect-ratio 16:9

Read the full file on GitHub · 100 lines

Files

What ships with it

1 file 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. 2d ago First seen · 100 lines · 66 tokens per session scan A 35bd064a7d3c

Subscribe to this mod's changes

video-generation is a skill published in the GitHub repository comisai/comis (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 66 tokens to every session and 878 once invoked, about $0.0003 per session on Opus 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.

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