Satūs is a Next.js starter template for building content-driven websites with React, Tailwind CSS, TypeScript, and optional integrations such as WebGL, Sanity, Shopify, HubSpot, and Mailchimp. Developers use it as a starting point for creating and deploying sites, while the catalogue add-ons provide project-specific coding guidance and workflows.
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 darkroomengineering/satus --skill next-bundle-optimizergit clone --depth 1 https://github.com/darkroomengineering/satusWrote 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/darkroomengineering/satus/next-bundle-optimizer)<a href="https://agentmods.dev/skills/darkroomengineering/satus/next-bundle-optimizer"><img src="https://agentmods.dev/badge/skills/darkroomengineering/satus/next-bundle-optimizer/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/darkroomengineering/satus/next-bundle-optimizer"><img src="https://agentmods.dev/badge/skills/darkroomengineering/satus/next-bundle-optimizer.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 | $0.00038 | $0.02455 |
| Opus 5.5 | $0.00015 | $0.00982 |
| Sonnet 5.5 | $0.00008 | $0.00491 |
| Haiku 4.5 | $0.00004 | $0.00246 |
Grade A, and why
next-bundle-optimizer 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.
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bundle optimizer
1. Set the scope
Analyze the whole app by default, covering all routes and shared client dependencies. Narrow the scope only when the user specifies a route, dependency, feature or other subset. Choose audit or fix mode. Audit is the default: generate analyzer artifacts and report candidates while leaving application source, dependencies and lockfiles unchanged. Fix mode requires an explicit request to change the app. Ask before changing visible behavior, timing, compatibility or a trust boundary. For a route's static App Shell, use next-cache-components-optimizer; install it first if unavailable (npx skills add https://github.com/vercel/next.js/tree/canary/skills/next-cache-components-optimizer). For navigation prefetch work, use next-partial-prefetching-optimizer; install it first if unavailable (npx skills add https://github.com/vercel/next.js/tree/canary/skills/next-partial-prefetching-optimizer).
Done: the whole-app or user-specified scope, mode and intended behavior are recorded. A request to capture or export data is audit mode, not permission to fix.
2. Capture and export a baseline
Run from the app directory with its package manager. Read next analyze --help for capture options and next analyze export --help for replay options in the installed CLI. Reuse a selected saved snapshot, or capture with a distinctive name first; then export it through gzip at its default compression level. Keep before/after .jsonl.gz files separate.
Sandbox requirement: If the agent’s sandbox blocks TCP port binding (as Codex’s does), it MUST run the next analyze --output capture outside the sandbox. Do not attempt the capture inside that sandbox, even though --output does not serve the analyzer UI.
Run the pipeline in Bash:
set -o pipefail
# Capture only when a new baseline is needed
pnpm exec next analyze --output --snapshot 'audit-before-unique-1'
pnpm exec next analyze export --snapshot 'audit-before-unique-1' | gzip > /tmp/analyze-app-before.jsonl.gz
What ships with it
3 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 · 107 lines · 38 tokens per session scan A a0cba357640f
next-bundle-optimizer is a skill published in the GitHub repository darkroomengineering/satus (1,012 stars, last pushed 2d ago), licensed MIT. It adds 38 tokens to every session and 2,455 once invoked, about $0.0002 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 2026-10-29.
Other skills, from other repositories
webgl-expert
Expert guide for WebGL API development including 3D graphics, shaders (GLSL), rendering pipeline, textures, buffers, performance optimization, and canvas rendering. Use when working with WebGL, 3D graphics, canvas rendering, shaders, GPU programming, or when user mentions WebGL, OpenGL ES, GLSL, vertex shaders…
lenis-react
Integrate Lenis smooth scroll into React and Next.js projects. Use when the user wants smooth scrolling, scroll-linked animations, parallax effects, GSAP ScrollTrigger sync, Framer Motion sync, programmatic scroll-to navigation, or scroll event listening in a React app. Covers ReactLenis provider setup, useLenis hook…
gsap-tackl
Implements and orchestrates GSAP in Tackl — useAnimation, useGSAP, ScrollTrigger, Lenis sync, page transitions, and reduced-motion fallbacks. Use when the user mentions GSAP, tweens, timelines, ScrollTrigger, scrub, matchMedia, Lenis, smooth scroll, page transitions, motion design, or enter/exit animations.
scss-modules
Styles React components with SCSS CSS Modules and the Tackl design system. Use when the user mentions styling, styles.module.scss, SCSS, CSS modules, design tokens, CSS variables, breakpoints (bp / bpd / mq), typography (t- classes, type mixins), spacing (data-pad / data-mar), the Waffl grid (Grid / Col), or theming…
tackl-performance
Optimizes Tackl apps for Web Vitals, reduced motion, and scroll performance. Use when the user mentions performance, LCP, CLS, prefers-reduced-motion, lazy loading, scroll jank, or PerformanceContext.
web-vitals-monitor
Monitor web vitals monitor operations. Auto-activating skill for Frontend Development.