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.
npx skills add WU-HAOTIAN34/2dimg2motion --skill img2mo-stdgit clone --depth 1 https://github.com/WU-HAOTIAN34/2dimg2motionWrote 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.
[](https://agentmods.dev/skills/wu-haotian34/2dimg2motion/img2mo-std)<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.
<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>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once 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 |
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.
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:
- If it is an existing relative or absolute path, use it directly.
- If it is a bare file name such as
s7.png, first trysample\s7.png. - If it has no extension such as
s7, first trysample\s7.png, thensample\s7.jpg, thensample\s7.webp. - 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
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.
- 10d ago First seen · 89 lines · 87 tokens per session scan A 76f36e8d7540
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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