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-managementgit 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-management)<a href="https://agentmods.dev/skills/dylantarre/animation-principles/attention-management"><img src="https://agentmods.dev/badge/skills/dylantarre/animation-principles/attention-management/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-management"><img src="https://agentmods.dev/badge/skills/dylantarre/animation-principles/attention-management.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 | $0.00022 | $0.00607 |
| Opus 5 | $0.00011 | $0.00303 |
| Sonnet 5 | $0.00004 | $0.00121 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
attention-management 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 9d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attention Management
Direct user focus correctly using Disney's principles.
Problem Indicators
- Users miss important content
- Decorative elements steal focus
- CTAs don't stand out
- Users look at wrong things first
- Information hierarchy is unclear
Diagnosis by Principle
Staging
Issue: Multiple elements compete for attention Fix: One thing moves at a time. Animate the most important element; keep others still.
Timing
Issue: Everything animates at same speed Fix: Primary content: faster animation. Secondary: slower or delayed. Speed implies importance.
Exaggeration
Issue: Uniform motion across hierarchy Fix: Important elements get more dramatic animation. Background elements get subtle motion.
Anticipation
Issue: No buildup directs eyes Fix: Use anticipation to guide attention. A small movement can draw eyes before the main action.
Appeal
Issue: Wrong elements are visually interesting Fix: Make important elements the most visually appealing. Animation should enhance hierarchy, not fight it.
Quick Fixes
- One animation at a time - Sequence, don't parallelize
- Stagger by importance - Most important animates first
- Reduce decorative motion - Background should be calm
- Increase CTA animation contrast - Stands out from surroundings
- Use motion to guide reading order - Top-to-bottom, left-to-right
Troubleshooting Checklist
- What do users look at first? (Eye tracking or testing)
- Does animation sequence match importance hierarchy?
- Are decorative animations subtle enough?
- Does primary CTA have strongest motion?
- Count simultaneous animations (should be 1-2)
- Test: Hide animation—does hierarchy still work?
- Is motion guiding or distracting?
- Does stillness create emphasis where needed?
Code Pattern
/* Stagger by importance */
.hero-title {
animation: fadeInUp 400ms ease-out;
}
.hero-subtitle {
animation: fadeInUp 400ms ease-out 100ms backwards;
}
.hero-cta {
animation: fadeInUp 400ms ease-out 200ms backwards,
pulse 2s ease-in-out 1s infinite;
}
/* De-emphasize background */
.background-element {
animation: subtleDrift 20s linear infinite;
opacity: 0.3;
}
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.
- 9d ago First seen · 90 lines · 22 tokens per session scan A de033ff8b898
attention-management is a skill published in the GitHub repository dylantarre/animation-principles (81 stars, last pushed 8mo ago), licensed MIT. It adds 22 tokens to every session and 607 once invoked, about $0.0001 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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