attention-grabbers

attention-grabbers is a skill for Claude Code, Codex from dylantarre/animation-principles. It costs 33 tokens per session (980 once invoked), scanned A, original, MIT.

A guide to animations that draw attention to interface elements such as badges, alerts, feature highlights, and banners.

In plain words
What is it for?
Use it to design pulses, shakes, glows, timing, repetition, and stopping rules for notifications, errors, promotions, and other attention signals.
Why use it?
It helps motion attract notice without making the interface confusing or unnecessarily distracting.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to design pulses, shakes, glows, timing, repetition, and stopping rules for notifications, errors, promotions, and other attention signals.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dylantarre/animation-principles/attention-grabbers
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 dylantarre/animation-principles --skill attention-grabbers
Clone the repo
git clone --depth 1 https://github.com/dylantarre/animation-principles

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 attention-grabbers

README.md
[![agentmods](https://agentmods.dev/badge/skills/dylantarre/animation-principles/attention-grabbers/github.svg)](https://agentmods.dev/skills/dylantarre/animation-principles/attention-grabbers)
Your own site
<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.

agentmods 80×15 button for attention-grabbers

Your own site · 80×15
<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>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 980 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
  • Socket pass 18 Mar 2026
  • Snyk pass 15 Feb 2026
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 $0.00033 $0.00980
Opus 5 $0.00016 $0.00490
Sonnet 5 $0.00007 $0.00196
Haiku 4.5 $0.00003 $0.00098

Measured 12d ago against content hash ff686002b720, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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.

skills/05-by-animation-type/attention-grabbers/SKILL.md · 125 lines

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); }
}

Read the full file on GitHub · 125 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. 12d ago First seen · 125 lines · 33 tokens per session scan A ff686002b720

Subscribe to this mod's changes

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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