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 Ertinox7711/SGRR-AGI-V2 --skill gsapgit clone --depth 1 https://github.com/Ertinox7711/SGRR-AGI-V2Wrote 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/ertinox7711/sgrr-agi-v2/gsap)<a href="https://agentmods.dev/skills/ertinox7711/sgrr-agi-v2/gsap"><img src="https://agentmods.dev/badge/skills/ertinox7711/sgrr-agi-v2/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/ertinox7711/sgrr-agi-v2/gsap"><img src="https://agentmods.dev/badge/skills/ertinox7711/sgrr-agi-v2/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 | $0.00065 | $0.02157 |
| Opus 5 | $0.00032 | $0.01078 |
| Sonnet 5 | $0.00013 | $0.00431 |
| Haiku 4.5 | $0.00006 | $0.00216 |
Grade A, and why
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 3d 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.
This is a copy
100% identical to gsap — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GSAP
HyperFrames Contract
HyperFrames controls GSAP through its gsap runtime adapter. Create a paused timeline synchronously, register it on window.__timelines with the exact data-composition-id, and let HyperFrames seek it.
<script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/gsap.min.js"></script>
<script>
window.__timelines = window.__timelines || {};
const tl = gsap.timeline({ paused: true });
tl.from(".title", { y: 48, opacity: 0, duration: 0.6, ease: "power3.out" }, 0);
tl.to(".accent", { scaleX: 1, duration: 0.5, ease: "power2.out" }, 0.25);
window.__timelines["main"] = tl; // key must equal data-composition-id on the composition root
</script>
- The registry key must match the composition root's
data-composition-id. - Do not call
tl.play()for render-critical motion. - Do not build timelines inside async code, timers, or event handlers.
- Keep loops finite. HyperFrames renders finite video durations.
Core Tween Methods
- gsap.to(targets, vars) — animate from current state to
vars. Most common. - gsap.from(targets, vars) — animate from
varsto current state (entrances). - gsap.fromTo(targets, fromVars, toVars) — explicit start and end.
- gsap.set(targets, vars) — apply immediately (duration 0).
Always use camelCase property names (e.g. backgroundColor, rotationX).
Common vars
- duration — seconds (default 0.5).
- delay — seconds before start.
- ease —
"power1.out"(default),"power3.inOut","back.out(1.7)","elastic.out(1, 0.3)","none". - stagger — number
0.1or object:{ amount: 0.3, from: "center" },{ each: 0.1, from: "random" }. - overwrite —
false(default),true, or"auto". - repeat — finite number; never
-1in HyperFrames. Compute repeats from the visible duration. yoyo — alternates direction with repeat. - onComplete, onStart, onUpdate — callbacks.
- immediateRender — default
truefor from()/fromTo(). Setfalseon later tweens targeting the same property+element to avoid overwrite.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 241 lines · 65 tokens per session scan A d65cfadd0040
gsap is a skill published in the GitHub repository Ertinox7711/SGRR-AGI-V2 (1 stars, last pushed 4d ago), licensed MIT. It adds 65 tokens to every session and 2,157 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to gsap, differing in 0 lines, and is treated as a copy.
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