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 dylantarre/animation-principles --skill universal-emotiongit clone --depth 1 https://github.com/dylantarre/animation-principlesWrote 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/dylantarre/animation-principles/universal-emotion)<a href="https://agentmods.dev/skills/dylantarre/animation-principles/universal-emotion"><img src="https://agentmods.dev/badge/skills/dylantarre/animation-principles/universal-emotion/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/dylantarre/animation-principles/universal-emotion"><img src="https://agentmods.dev/badge/skills/dylantarre/animation-principles/universal-emotion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk 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 | $0.00030 | $0.00818 |
| Opus 5 | $0.00015 | $0.00409 |
| Sonnet 5 | $0.00006 | $0.00164 |
| Haiku 4.5 | $0.00003 | $0.00082 |
Grade A, and why
universal-emotion 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 7d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Universal Emotion Animation Framework
Map Disney's 12 principles to any emotional goal through systematic analysis.
Emotional Goal
Any emotion can be achieved through intentional application of animation principles. This framework helps translate emotional intent into specific motion parameters.
Emotion Mapping Framework
Step 1: Define the Emotion
Identify your target on these spectrums:
- Energy: Low ←→ High
- Valence: Negative ←→ Positive
- Arousal: Calm ←→ Excited
- Dominance: Submissive ←→ Powerful
Step 2: Map Principles to Emotion
| Principle | Low Energy | High Energy |
|---|---|---|
| Squash & Stretch | 0-10% | 20-40% |
| Anticipation | 50-100ms | 150-300ms |
| Timing | 400-800ms | 100-250ms |
| Exaggeration | 0-15% | 25-50% |
| Follow Through | Extended settle | Quick bounce |
| Principle | Serious | Playful |
|---|---|---|
| Arc | Direct/Linear | Curved/Bouncy |
| Secondary Action | Minimal | Abundant |
| Straight Ahead | Avoid | Embrace |
| Appeal | Clean/Geometric | Round/Organic |
Step 3: Select Easing
| Emotion Type | Easing Style | Example |
|---|---|---|
| Calm | Symmetric ease | ease-in-out |
| Confident | Strong ease-out | cubic-bezier(0,0,0.2,1) |
| Playful | Overshoot | cubic-bezier(0.34,1.56,0.64,1) |
| Urgent | Sharp ease-out | cubic-bezier(0.0,0,0.2,1) |
| Elegant | Extended ease | cubic-bezier(0.4,0,0.6,1) |
Quick Reference by Emotion
Positive Emotions
- Joy: Fast timing, high squash/stretch, bouncy easing
- Trust: Consistent timing, minimal deformation, smooth easing
- Calm: Slow timing, subtle movement, symmetric easing
- Excitement: Fast timing, high energy, dynamic easing
Functional Emotions
- Urgency: Very fast, direct paths, attention-grabbing
- Professional: Moderate timing, minimal decoration, standard easing
- Friendly: Moderate timing, soft deformation, gentle easing
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.
- 7d ago First seen · 103 lines · 30 tokens per session scan A db992b315486
universal-emotion is a skill published in the GitHub repository dylantarre/animation-principles (80 stars, last pushed 8mo ago), licensed MIT. It adds 30 tokens to every session and 818 once invoked, about $0.0002 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 2026-09-03.
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