OpenFang is an open-source operating system for autonomous AI agents, built in Rust to run agents that perform scheduled work such as research, monitoring, lead generation, and reporting. It is for people who want agents to operate continuously rather than only respond to prompts. The catalogue add-ons extend workflows around the OpenFang agent system.
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 RightNow-AI/openfang --skill nextjs-expertgit clone --depth 1 https://github.com/RightNow-AI/openfangWrote 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/rightnow-ai/openfang/nextjs-expert)<a href="https://agentmods.dev/skills/rightnow-ai/openfang/nextjs-expert"><img src="https://agentmods.dev/badge/skills/rightnow-ai/openfang/nextjs-expert/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/rightnow-ai/openfang/nextjs-expert"><img src="https://agentmods.dev/badge/skills/rightnow-ai/openfang/nextjs-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector 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 | $0.00024 | $0.00650 |
| Opus 5.5 | $0.00010 | $0.00260 |
| Sonnet 5.5 | $0.00005 | $0.00130 |
| Haiku 4.5 | $0.00002 | $0.00065 |
Grade A, and why
nextjs-expert 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- nextjs-expert — 100% identical, 0 lines differ
- nextjs-expert — 98% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Next.js Expert
A seasoned Next.js architect with deep expertise in the App Router paradigm, server-side rendering strategies, and production deployment patterns. This skill provides guidance on building performant, SEO-friendly web applications using Next.js 14+ conventions, including Server Components, Streaming, and the full spectrum of data fetching and caching mechanisms.
Key Principles
- Prefer Server Components by default; only add "use client" when the component requires browser APIs, event handlers, or React state
- Leverage the app/ directory structure where each folder segment maps to a URL route, using layout.tsx for shared UI and page.tsx for unique content
- Design data fetching at the server layer using async Server Components and fetch with Next.js caching semantics
- Use generateStaticParams for static pre-rendering of dynamic routes at build time, falling back to on-demand ISR for long-tail pages
- Keep client bundles small by pushing logic into Server Components and using dynamic imports for heavy client-only libraries
Techniques
- Structure routes with app/[segment]/page.tsx, using route groups (parentheses) to organize without affecting URL paths
- Implement loading.tsx and error.tsx boundaries at each route segment to provide instant loading states and graceful error recovery
- Use Route Handlers (app/api/.../route.ts) with exported GET, POST, PUT, DELETE functions for API endpoints
- Configure middleware in middleware.ts at the project root with a matcher config to intercept requests for auth, redirects, or header injection
- Optimize images with next/image (automatic srcSet, lazy loading, AVIF/WebP) and fonts with next/font (zero layout shift, self-hosted subsets)
- Enable ISR by returning revalidate values from fetch calls or using revalidatePath/revalidateTag for on-demand cache invalidation
- Set up next.config.js with redirects, rewrites, headers, and the experimental options appropriate to your deployment target
Common Patterns
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 · 40 lines · 24 tokens per session scan A 36f863392299
nextjs-expert is a skill published in the GitHub repository RightNow-AI/openfang (18,220 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 24 tokens to every session and 650 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 2026-08-30.
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