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 perniemann/pnCore --skill pn-gsapgit clone --depth 1 https://github.com/perniemann/pnCoreWrote 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/perniemann/pncore/pn-gsap)<a href="https://agentmods.dev/skills/perniemann/pncore/pn-gsap"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-gsap/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/perniemann/pncore/pn-gsap"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-gsap.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00069 | $0.02969 |
| Opus 5.5 | $0.00028 | $0.01188 |
| Sonnet 5.5 | $0.00014 | $0.00594 |
| Haiku 4.5 | $0.00007 | $0.00297 |
Grade A, and why
pn-gsap 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 1mo 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 — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GSAP deep API
When to use
- Writing or debugging GSAP timelines, tweens, or ScrollTrigger sequences.
- Choosing the right plugin (SplitText, Flip, DrawSVG, MorphSVG, MotionPath, etc.).
- Integrating GSAP inside a framework (React / Vue / Svelte) correctly.
- Recording GSAP animations deterministically as video via a Frame Adapter (see
pn-html-to-video). - Auditing performance: GPU compositing,
will-changeusage, ticker frequency.
For motion role taxonomy (Reveal / Orient / Confirm / Delight), motion budgets, and prefers-reduced-motion requirements, load pn-animation alongside this skill.
Install
npm install gsap # core + all free plugins (ScrollTrigger, Draggable, Observer, etc.)
npm install @gsap/react # useGSAP hook for React
Club plugins (SplitText, Flip, DrawSVG, MorphSVG, MotionPath, ScrambleText, GSDevTools) require a GSAP Club or Business licence. Import from the gsap/dist/ bundle or from the npm-authenticated @gsap/ scoped package.
Core API
Tween
import { gsap } from 'gsap';
// from — animate from these values to current
gsap.from('.hero', { opacity: 0, y: 40, duration: 0.7, ease: 'power3.out' });
// to — animate from current to these values
gsap.to('.card', { scale: 1.04, duration: 0.2, ease: 'power2.out' });
// fromTo — explicit start and end (frame-accurate; preferred in video adapters)
gsap.fromTo('.title',
{ opacity: 0, y: 32 },
{ opacity: 1, y: 0, duration: 0.8, ease: 'power3.out' }
);
// set — instant (no duration); use for initial state before timeline plays
gsap.set('.nav', { opacity: 0, y: -16 });
Timeline
const tl = gsap.timeline({ defaults: { ease: 'power3.out', duration: 0.6 } });
tl.from('.hero-heading', { opacity: 0, y: 40 })
.from('.hero-sub', { opacity: 0, y: 24 }, '-=0.4') // 0.4s overlap
.from('.hero-cta', { opacity: 0, scale: 0.9 }, '-=0.3')
.from('.hero-image', { opacity: 0, x: 60 }, '<'); // same start as previous
// Label-based positioning
tl.addLabel('features', 2)
.from('.feature-card', { opacity: 0, y: 32, stagger: 0.1 }, 'features');
// Repeat and yoyo
const loop = gsap.timeline({ repeat: -1, yoyo: true });
loop.to('.pulse-dot', { scale: 1.3, duration: 0.8, ease: 'sine.inOut' });
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.
- 1mo ago First seen · 329 lines · 69 tokens per session scan A c65ad5d44c5a
pn-gsap is a skill published in the GitHub repository perniemann/pnCore (0 stars, last pushed 2d ago), licensed MIT. It adds 69 tokens to every session and 2,969 once invoked, about $0.0003 per session on Opus 5.5. 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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