img2mo-learn

img2mo-learn is a skill for Claude Code, Codex from WU-HAOTIAN34/2dimg2motion. It costs 104 tokens per session (1,622 once invoked), scanned A, original, MIT.

A skill that studies videos, animation frames, spritesheets, Spine assets, and other motion references, then saves reusable knowledge about the animation in the project.

In plain words
What is it for?
Use it to examine timing, poses, movement style, and related details from supplied motion resources and store the results in the project's knowledge folder.
Why use it?
It preserves observations from working or failed motion examples so later animation work can reuse them instead of starting from memory.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

Good fit Use it to examine timing, poses, movement style, and related details from supplied motion resources and store the results in the project's knowledge folder.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wu-haotian34/2dimg2motion/img2mo-learn
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-learn
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-learn

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/wu-haotian34/2dimg2motion/img2mo-learn"><img src="https://agentmods.dev/badge/skills/wu-haotian34/2dimg2motion/img2mo-learn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 104 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,622 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 warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium System Prompt Leakage · line 79
    Skill contains patterns that could indirectly extract system prompts through rephrasing, translation, summarization, or side-channel techniques.
    Fix: Guard against indirect extraction by refusing to summarize, translate, or rephrase system instructions. Add explicit anti-extraction clauses.
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 $0.00104 $0.01622
Opus 5 $0.00052 $0.00811
Sonnet 5 $0.00021 $0.00324
Haiku 4.5 $0.00010 $0.00162

Measured 11d ago against content hash bed5970054e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

img2mo-learn 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 11d 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-learn/SKILL.md · 144 lines

How it starts

The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Img2mo-learn

Overview

Use this skill when the user invokes:

/img2mo-learn <resource-path-or-folder>
img2mo-learn <resource-path-or-folder>

The goal is to turn finished or reference motion assets into reusable project knowledge. Store learned knowledge in the project-level img2mo-knowledge/ folder, never in the installed Codex skill directory during normal work.

Input Resolution

Resolve the argument after img2mo-learn as follows:

  1. If it is an existing relative or absolute path, use it directly.
  2. If it is a bare name, first try sample\<name>, then output\<name>, then motion\<name>.
  3. If it is a folder, inspect likely assets in this order: manifest.json, preview.gif, contact-sheet.*, spritesheet.*, fullframe/, frames/, Spine .json/.atlas/.skel, then videos.
  4. If no matching resource exists, report the missing path and ask for the correct path.

Supported resources:

  • video files such as .mp4, .mov, .webm;
  • PNG frame folders, spritesheets, contact sheets, or GIF previews;
  • project outputs from this skill such as output/<action-id>/;
  • Spine-style assets such as .json, .atlas, .skel, texture folders;
  • local reference-library folders under motion/.

Knowledge Location

Create this structure if missing:

img2mo-knowledge/
|-- index.md
|-- learnings.jsonl
|-- action-patterns.md
|-- style-patterns.md
|-- prompt-patterns.md
`-- failures.md

Append one JSON object per learning session to img2mo-knowledge/learnings.jsonl. Keep Markdown files concise and curated; do not paste huge logs, full prompts, or complete frame listings.

Learning Workflow

  1. Identify the resource type.
    • For video: read frame size, fps, duration, and frame count with ffprobe when available.
    • For frame sequences: count frames, inspect canvas sizes, alpha/background, and contact sheet if present.
    • For spritesheets: infer grid/cell count when possible; otherwise describe visible beats.
    • For Spine assets: inspect animation names, bone/slot names, skins, attachments, timeline names, and texture organization without assuming rendered motion if frames are not available.

Read the full file on GitHub · 144 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. 11d ago First seen · 144 lines · 104 tokens per session scan A bed5970054e9

Subscribe to this mod's changes

img2mo-learn is a skill published in the GitHub repository WU-HAOTIAN34/2dimg2motion (190 stars, last pushed 2mo ago), licensed MIT. It adds 104 tokens to every session and 1,622 once invoked, about $0.0005 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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