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 agentmods add skills/guillermoscript/lms-front/animatenpx skills add guillermoscript/lms-front --skill animategit clone --depth 1 https://github.com/guillermoscript/lms-frontWhat 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 | $0.00025 | $0.01895 |
| Opus 5 | $0.00013 | $0.00948 |
| Sonnet 5 | $0.00005 | $0.00379 |
| Haiku 4.5 | $0.00003 | $0.00189 |
Grade A, and why
animate 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.
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.
This is a copy
100% identical to animate — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze a feature and strategically add animations and micro-interactions that enhance understanding, provide feedback, and create delight.
MANDATORY PREPARATION
Context Gathering (Do This First)
You cannot do a great job without having necessary context, such as target audience (critical), desired use-cases (critical), brand personality/tone (playful vs serious, energetic vs calm), and performance constraints.
Attempt to gather these from the current thread or codebase.
- If you don't find exact information and have to infer from existing design and functionality, you MUST STOP and STOP and call the AskUserQuestionTool to clarify. whether you got it right.
- Otherwise, if you can't fully infer or your level of confidence is medium or lower, you MUST STOP and call the AskUserQuestionTool to clarify. clarifying questions first to complete your context.
Do NOT proceed until you have answers. Guessing leads to inappropriate or excessive animation.
Use frontend-design skill
Use the frontend-design skill for design principles and anti-patterns. Do NOT proceed until it has executed and you know all DO's and DON'Ts.
Assess Animation Opportunities
Analyze where motion would improve the experience:
-
Identify static areas:
- Missing feedback: Actions without visual acknowledgment (button clicks, form submission, etc.)
- Jarring transitions: Instant state changes that feel abrupt (show/hide, page loads, route changes)
- Unclear relationships: Spatial or hierarchical relationships that aren't obvious
- Lack of delight: Functional but joyless interactions
- Missed guidance: Opportunities to direct attention or explain behavior
-
Understand the context:
- What's the personality? (Playful vs serious, energetic vs calm)
- What's the performance budget? (Mobile-first? Complex page?)
- Who's the audience? (Motion-sensitive users? Power users who want speed?)
- What matters most? (One hero animation vs many micro-interactions?)
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.
- 2d ago First seen · 190 lines · 25 tokens per session scan A 7a523bffd032
animate is a skill published in the GitHub repository guillermoscript/lms-front (24 stars, last pushed 2d ago), licensed MIT. It adds 25 tokens to every session and 1,895 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to animate, differing in 0 lines, and is treated as a copy.
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review-animations
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teach-me
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a2tl-video
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