img2mo-std

img2mo-std is a skill for Claude Code, Codex from WU-HAOTIAN34/2dimg2motion. It costs 87 tokens per session (795 once invoked), scanned A, original, MIT.

An image-preparation tool for making a 2D character, creature, prop, or weapon image ready for animation. It checks the source and creates a smaller image with a transparent canvas and extra space around the subject.

In plain words
What is it for?
Use it to prepare baseline images for walking, attacking, idling, weapon swings, or movements involving capes, tails, horns, limbs, and effects.
Why use it?
Animation poses can extend beyond a tightly cropped or edge-touching image, and solid backgrounds can cause problems. This prepares a consistent starting frame before generating motion.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to prepare baseline images for walking, attacking, idling, weapon swings, or movements involving capes, tails, horns, limbs, and effects.

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Install with agentmods
npx agentmods add skills/wu-haotian34/2dimg2motion/img2mo-std
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 WU-HAOTIAN34/2dimg2motion --skill img2mo-std
Clone the repo
git clone --depth 1 https://github.com/WU-HAOTIAN34/2dimg2motion

Made for: Claude Code, Codex.

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 img2mo-std

README.md
[![agentmods](https://agentmods.dev/badge/skills/wu-haotian34/2dimg2motion/img2mo-std/github.svg)](https://agentmods.dev/skills/wu-haotian34/2dimg2motion/img2mo-std)
Your own site
<a href="https://agentmods.dev/skills/wu-haotian34/2dimg2motion/img2mo-std"><img src="https://agentmods.dev/badge/skills/wu-haotian34/2dimg2motion/img2mo-std/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 img2mo-std

Your own site · 80×15
<a href="https://agentmods.dev/skills/wu-haotian34/2dimg2motion/img2mo-std"><img src="https://agentmods.dev/badge/skills/wu-haotian34/2dimg2motion/img2mo-std.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 795 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00087 $0.00795
Opus 5 $0.00044 $0.00398
Sonnet 5 $0.00017 $0.00159
Haiku 4.5 $0.00009 $0.00080

Measured 10d ago against content hash 76f36e8d7540, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

img2mo-std 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 10d 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/img2mo-std/SKILL.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Img2mo-std

Overview

Use this skill when the user invokes:

/img2mo-std xxx.png/pos

The command audits and standardizes a baseline frame before animation generation. It creates a smaller, padded, transparent-canvas source image that leaves enough room for walk, attack, idle, weapon swing, cape, tail, horn, or limb stretch poses.

Input Resolution

Resolve the argument after /img2mo-std as follows:

  1. If it is an existing relative or absolute path, use it directly.
  2. If it is a bare file name such as s7.png, first try sample\s7.png.
  3. If it has no extension such as s7, first try sample\s7.png, then sample\s7.jpg, then sample\s7.webp.
  4. If no matching image exists, report the missing path and do not guess from unrelated files.

Examples:

/img2mo-std s7
/img2mo-std s7.png
/img2mo-std sample\s7.png
/img2mo-std C:\AI\2dimg2motion-v1\sample\s7.png

Audit Criteria

A baseline is not standard if any of these are true:

  • The foreground subject is larger than about 300-400 px on its longest side.
  • The subject touches or nearly touches the canvas edge.
  • There is not enough empty transparent space for arms, legs, weapons, tails, capes, horns, or effects to extend during motion.
  • The background is opaque white or near-white when the character should be isolated.
  • The source has a huge canvas that will slow generation without adding useful detail.
  • Previous generated frames show inconsistent character size, off-center motion, clipped body parts, or crowded sprite-sheet cells.

Tool

Run the repository tool from the workspace root after resolving the image path:

python scripts\standardize_baseline.py <resolved-image-path>

Default output:

sample\<input-stem>-standard.png

Useful options:

python scripts\standardize_baseline.py sample\s7.png --subject-max 360 --margin-ratio 0.75
python scripts\standardize_baseline.py sample\s7.png --output sample\s7-standard.png
python scripts\standardize_baseline.py sample\s7.png --check-only

Read the full file on GitHub · 89 lines

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. 10d ago First seen · 89 lines · 87 tokens per session scan A 76f36e8d7540

Subscribe to this mod's changes

img2mo-std is a skill published in the GitHub repository WU-HAOTIAN34/2dimg2motion (190 stars, last pushed 2mo ago), licensed MIT. It adds 87 tokens to every session and 795 once invoked, about $0.0004 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 2026-08-30.

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