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 healthcare-medicalgit 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/healthcare-medical)<a href="https://agentmods.dev/skills/dylantarre/animation-principles/healthcare-medical"><img src="https://agentmods.dev/badge/skills/dylantarre/animation-principles/healthcare-medical/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/healthcare-medical"><img src="https://agentmods.dev/badge/skills/dylantarre/animation-principles/healthcare-medical.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 | $0.00023 | $0.00730 |
| Opus 5 | $0.00012 | $0.00365 |
| Sonnet 5 | $0.00005 | $0.00146 |
| Haiku 4.5 | $0.00002 | $0.00073 |
Grade A, and why
healthcare-medical 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Healthcare & Medical Animation Principles
Apply Disney's 12 principles to create calming, trustworthy experiences that prioritize clarity and reduce anxiety.
The 12 Principles Applied
1. Squash & Stretch
- Minimal Use: Avoid playful squash on health data
- Breathing Exercises: Gentle expand/contract for guided breathing
- Heart Rate: Subtle pulse matching actual rhythm
2. Anticipation
- Appointment Booking: Brief preparation before confirmation
- Test Results: Thoughtful pause before revealing sensitive data
- Medication Reminders: Gentle fade-in, never jarring
3. Staging
- Critical Alerts: Center stage with clear hierarchy
- Vital Signs: Most important metrics prominently displayed
- Privacy First: Blur or hide sensitive info until focused
4. Straight Ahead & Pose to Pose
- Health Journeys: Step-by-step progress (pose to pose)
- Real-time Monitoring: Continuous data streams (straight ahead)
- Onboarding: Clear sequential steps
5. Follow Through & Overlapping Action
- Dashboard Load: Cards appear in logical health order
- Prescription Updates: Medicine icon settles before details
- Chart Animations: Data points connect sequentially
6. Slow In & Slow Out
- All Transitions: Gentle easing, never abrupt
- Modal Reveals: Soft fade-in for sensitive information
- Navigation: Smooth 400-500ms transitions
7. Arc
- Progress Indicators: Circular arcs for completion
- Body Diagrams: Smooth paths between body regions
- Timeline Navigation: Curved paths through health history
8. Secondary Action
- Confirmation Checkmarks: Gentle pulse after booking
- Loading States: Calming animations during data fetch
- Success States: Subtle color transitions
9. Timing
- Slower Overall: 400-600ms for calm, measured feel
- Critical Alerts: Faster 200ms to ensure attention
- Data Entry: Responsive 150ms feedback
10. Exaggeration
- Avoid in Most Cases: Medical context requires restraint
- Emergency Only: Reserved for urgent alerts
- Celebrations: Subtle for health milestones
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 · 84 lines · 23 tokens per session scan A 64c16f4b7025
healthcare-medical is a skill published in the GitHub repository dylantarre/animation-principles (81 stars, last pushed 8mo ago), licensed MIT. It adds 23 tokens to every session and 730 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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