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 attention-grabbersgit 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/attention-grabbers)<a href="https://agentmods.dev/skills/dylantarre/animation-principles/attention-grabbers"><img src="https://agentmods.dev/badge/skills/dylantarre/animation-principles/attention-grabbers/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/attention-grabbers"><img src="https://agentmods.dev/badge/skills/dylantarre/animation-principles/attention-grabbers.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 | $0.00033 | $0.00980 |
| Opus 5 | $0.00016 | $0.00490 |
| Sonnet 5 | $0.00007 | $0.00196 |
| Haiku 4.5 | $0.00003 | $0.00098 |
Grade A, and why
attention-grabbers 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 12d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attention-Grabbing Animations
Apply Disney's 12 principles to focus-drawing motion.
Principle Application
Squash & Stretch: Pulsing scale draws attention. 1.0 → 1.1 → 1.0 cycle catches peripheral vision.
Anticipation: Brief pause before attention animation. Let it build then release.
Staging: Position attention elements where users will see them. Corner badges, inline highlights.
Straight Ahead vs Pose-to-Pose: Design attention states: rest, active/pulsing, acknowledged.
Follow Through & Overlapping: Badge pulses, then count updates. Stagger the attention signals.
Slow In/Slow Out: Ease in/out on pulses. Smooth oscillation is less jarring than sharp bounces.
Arcs: Shake animations follow arc patterns. Left-right with slight vertical oscillation.
Secondary Action: Pulse + glow + color shift for maximum attention (use sparingly).
Timing:
- Single attention grab: 300-500ms
- Repeating pulse: 2000-3000ms cycle
- Urgent pulse: 1000-1500ms cycle
- Decay: Stop after 3-5 cycles or 10 seconds
Exaggeration: This is where exaggeration shines. Scale to 1.2, bright colors, bold motion.
Solid Drawing: Attention elements must still feel part of the UI, not floating or detached.
Appeal: Attention should feel like helpful notification, not aggressive demand.
Timing Recommendations
| Attention Type | Duration | Cycles | Decay |
|---|---|---|---|
| Badge Pulse | 300ms | 2-3 | Stop after animation |
| Notification Dot | 2000ms | 3 | 6 seconds total |
| New Feature | 500ms | 2 | Stay subtle |
| Error Shake | 400ms | 1 | None |
| Urgent Alert | 1000ms | infinite | Until dismissed |
| Promotional | 3000ms | 2 | 6 seconds |
Implementation Patterns
/* Pulse attention */
.badge-pulse {
animation: pulse 2000ms ease-in-out 3;
}
@keyframes pulse {
0%, 100% { transform: scale(1); }
50% { transform: scale(1.15); }
}
/* Subtle glow */
.glow-attention {
animation: glow 2000ms ease-in-out 3;
}
@keyframes glow {
0%, 100% { box-shadow: 0 0 0 0 rgba(59, 130, 246, 0); }
50% { box-shadow: 0 0 0 8px rgba(59, 130, 246, 0.3); }
}
/* Error shake */
.shake {
animation: shake 400ms ease-in-out;
}
@keyframes shake {
0%, 100% { transform: translateX(0); }
20%, 60% { transform: translateX(-8px); }
40%, 80% { transform: translateX(8px); }
}
/* Ring animation (notification) */
.ring {
animation: ring 2500ms ease-in-out 2;
}
@keyframes ring {
0%, 100% { transform: rotate(0); }
10%, 30% { transform: rotate(10deg); }
20%, 40% { transform: rotate(-10deg); }
50%, 100% { transform: rotate(0); }
}
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.
- 12d ago First seen · 125 lines · 33 tokens per session scan A ff686002b720
attention-grabbers is a skill published in the GitHub repository dylantarre/animation-principles (80 stars, last pushed 8mo ago), licensed MIT. It adds 33 tokens to every session and 980 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 2026-08-30.
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