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 monoes/monomind --skill monomotiongit clone --depth 1 https://github.com/monoes/monomindWrote 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/monoes/monomind/monomotion)<a href="https://agentmods.dev/skills/monoes/monomind/monomotion"><img src="https://agentmods.dev/badge/skills/monoes/monomind/monomotion/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/monoes/monomind/monomotion"><img src="https://agentmods.dev/badge/skills/monoes/monomind/monomotion.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 | $0.00034 | $0.01060 |
| Opus 5.5 | $0.00014 | $0.00424 |
| Sonnet 5.5 | $0.00007 | $0.00212 |
| Haiku 4.5 | $0.00003 | $0.00106 |
Grade A, and why
monomotion 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 2d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monomotion — HTML Animation with GSAP
API-controllable, HTML-native animation using GSAP. No React, no video rendering — animations run live in the browser and are fully controllable via JavaScript API, WebSocket, or REST.
Core Philosophy
- Animations are timelines — sequences of tweens with precise timing
- Timelines are pausable, seekable, reversible at any point
- Control surfaces (API, WebSocket, UI) are decoupled from animation definitions
- CSS transitions and keyframes are not used — GSAP owns all motion
Setup
<!-- CDN — drop into any HTML file -->
<script src="https://cdn.jsdelivr.net/npm/gsap@3/dist/gsap.min.js"></script>
<!-- With ScrollTrigger plugin -->
<script src="https://cdn.jsdelivr.net/npm/gsap@3/dist/ScrollTrigger.min.js"></script>
# npm install
npm install gsap
import { gsap } from "gsap";
Basic Timeline
const tl = gsap.timeline({ paused: true });
tl.to(".box", { x: 200, duration: 0.8, ease: "power2.out" })
.to(".box", { opacity: 0, duration: 0.4 }, "+=0.2")
.from(".title", { y: -50, autoAlpha: 0, duration: 0.6 }, "<");
Position parameter shortcuts:
"+=0.2"— 0.2s after previous tween ends"-=0.1"— 0.1s before previous tween ends"<"— same start time as previous tween"1.5"— absolute 1.5s mark in timeline
Playback Control API
tl.play(); // play forward from current position
tl.pause(); // freeze
tl.resume(); // resume from paused position
tl.reverse(); // play backward from current position
tl.restart(); // jump to start and play
tl.seek(1.5); // jump to 1.5s (no play)
tl.progress(0.5); // jump to 50% of total duration
tl.timeScale(2); // 2× speed
tl.timeScale(0.5); // half speed
// Read state
tl.time(); // current time in seconds
tl.progress(); // 0–1
tl.duration(); // total duration
tl.isActive(); // true if currently playing
What ships with it
7 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.
- 2d ago First seen · 146 lines · 34 tokens per session scan A d1beffcc6e5f
monomotion is a skill published in the GitHub repository monoes/monomind (23 stars, last pushed 2d ago), licensed Apache-2.0. It adds 34 tokens to every session and 1,060 once invoked, about $0.0001 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 2026-10-26.
Other skills, from other repositories
compare-harnesses
Diff two scaffolded harnesses (ADR-031). Reports manifest meta drift + host list + per-file fingerprint changes (added/removed/changed). Exits 0 IDENTICAL, 1 DRIFT, 2 missing manifest. Use --bundle for the ADR-031 schema-1 JSON envelope.
create-harness
Scaffold your own focused AI agent harness — pick host (Claude Code, Codex, pi.dev, Hermes), template, agents, skills, and ship a npm-publishable harness with its own npx CLI. Use when a user asks to "create my own agent harness", "scaffold a harness", "make a custom Claude Code plugin like ruflo", or "build a…
diag-harness
Kernel-version skew check (ADR-027). Reports manifest surface + manifest kernel + installed kernel + verdict (match/patch-diff/minor-diff/major-diff). Exits 1 on minor/major skew with a copy-pasteable npm install @metaharness/[email protected] next step. Exits 2 if no .harness/manifest.json at path.
example-harness
Scaffold a ready-made AI agent harness in one command from the 19 published @metaharness/ example packages — 9 host integrations (Claude Code, Codex, Hermes, pi.dev, OpenClaw, RVM, Copilot, OpenCode, GitHub Actions) + 10 vertical pods (devops, research, trading, support, legal, coding, education, sales, gaming…
oia-manifest
Emit .harness/oia-manifest.json declaring layer alignment with the OIA v0.1 9-layer reference architecture. Self-describes the harness's MCP wiring, witness signing, audit log, identity posture (always 'none' at v0.1). --check verifies an existing manifest, --dry-run prints without writing, --json emits to stdout.
repo-genome
7-section readiness scorecard for a LOCAL repo. Reports repo type + agent topology + MCP risk + test confidence + release readiness + recommended harness plan + scorecard. Exit 0 ready, 1 needs-work, 2 blocked. --json for the 6-field scorecard, --bundle for the ADR-031 schema-1 envelope.