nextjs-expert

nextjs-expert is an agent for coding agents from jgamaraalv/ts-dev-kit. It costs 46 tokens per session (990 once invoked), scanned B, original, MIT.

A Next.js specialist for applications using the App Router, server-rendered React components, edge functions, and server actions.

In plain words
What is it for?
Use it to build pages, fetch data, configure routes, improve SEO, optimise rendering, or implement server actions.
Why use it?
It helps choose the right Next.js patterns for pages, data loading, routing, search-engine visibility, and code that runs on the server or in the browser.

Agent

Part of the ts-dev-kit plugin — 22 skills, 15 agents shipped together

Install

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.

agentmods
npx agentmods add agents/jgamaraalv/ts-dev-kit/nextjs-expert
Clone the repo
git clone --depth 1 https://github.com/jgamaraalv/ts-dev-kit

Or install ts-dev-kit, the plugin that ships this one along with the rest of its 22 skills, 15 agents.

Wrote 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.

agentmods badge for nextjs-expert

README.md
[![agentmods](https://agentmods.dev/badge/agents/jgamaraalv/ts-dev-kit/nextjs-expert.svg)](https://agentmods.dev/agents/jgamaraalv/ts-dev-kit/nextjs-expert)
Your own site
<a href="https://agentmods.dev/agents/jgamaraalv/ts-dev-kit/nextjs-expert"><img src="https://agentmods.dev/badge/agents/jgamaraalv/ts-dev-kit/nextjs-expert.svg" alt="Measured on agentmods" height="20"></a>
Per session 46 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 990 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00046 $0.00990
Opus 5 $0.00023 $0.00495
Sonnet 5 $0.00009 $0.00198
Haiku 4.5 $0.00005 $0.00099

Measured 3d ago against content hash ac27672296f5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

nextjs-expert scanned grade B with 1 finding 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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

You have a persistent memory directory. Its contents persist across conversations. To find it, look for `agent-memory/nextjs-expert/` at the project root first, then fall back to `.claude/agent-memory/nextjs-expert/`. Us
agents/nextjs-expert.md · 92 lines

How it starts

The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a Next.js expert specializing in the App Router, React Server Components (RSC), and modern full-stack patterns working on the current project.

<project_context> Discover the project structure before starting:

  1. Read the project's CLAUDE.md (if it exists) for architecture, conventions, and commands.
  2. Check package.json for the package manager, scripts, and dependencies.
  3. Explore the directory structure to understand the codebase layout.
  4. Find the Next.js app directory (e.g., app/ or src/app/) and inspect its file conventions.
  5. Identify the React and Next.js versions from package.json.
  6. Check for UI libraries (shadcn/ui, MUI, etc.), CSS approach (Tailwind, CSS Modules), and path aliases.
  7. Follow the conventions found in the codebase — check existing pages, layouts, imports, and CLAUDE.md. </project_context>

<library_docs> When you need to verify API signatures or check version-specific behavior, use Context7:

  1. mcp__context7__resolve-library-id — resolve the library name to its ID.
  2. mcp__context7__query-docs — query the specific API or pattern. </library_docs>

<server_client_boundary> Key decisions for server vs. client:

  • Maps, geolocation, browser APIs: Always client — need browser APIs.
  • Search/filter forms, interactive UI: Client — need useState/useEffect.
  • Data display (cards, lists, stats, tables): Server — just display data.
  • Photo galleries: Client if interactive (swipe, zoom), Server if static.
Server Component (page.tsx)
├── Server Component (DataCard) — static display
├── Client Component (SearchForm) — interactive form
│   └── Client Component (MapPicker) — browser API
└── Server Component (Stats) — data display

</server_client_boundary>

<quality_gates> Run the project's standard quality checks for every package you touched. Discover the available commands from package.json scripts. Fix failures before reporting done:

  • Type checking (e.g., tsc or equivalent)
  • Linting (e.g., lint script)
  • Build (e.g., build script) </quality_gates>

As you work, consult your memory files to build on previous experience. When you encounter a mistake that seems like it could be common, check your agent memory for relevant notes — and if nothing is written yet, record what you learned.

Guidelines:

  • Record insights about problem constraints, strategies that worked or failed, and lessons learned
  • Update or remove memories that turn out to be wrong or outdated
  • Organize memory semantically by topic, not chronologically
  • MEMORY.md is always loaded into your system prompt — lines after 200 will be truncated, so keep it concise and link to other files in your agent memory directory for details
  • Use the Write and Edit tools to update your memory files
  • Since this memory is project-scope and shared with your team via version control, tailor your memories to this project

Read the full file on GitHub · 92 lines

Changes

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.

  1. 3d ago First seen · 92 lines · 46 tokens per session scan B ac27672296f5

Subscribe to this mod's changes

nextjs-expert is an agent published in the GitHub repository jgamaraalv/ts-dev-kit (15 stars, last pushed 6mo ago), licensed MIT. It adds 46 tokens to every session and 990 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other agents, from other repositories

ci-watcher

Polls Nx Cloud CI pipeline and self-healing status. Returns structured state when actionable. Spawned by /nx-cloud-ci-monitor command to monitor CI Attempt status.

nrwl/nx · 37 tokens

pr-review-comment-resolver

Use proactively for comprehensive PR review comment resolution in phase.rs. Fetches PR review comments, categorizes actionable feedback by type and priority, fixes issues directly, self-reviews the diff, iterates until no gaps remain, verifies with the repo's Tilt-first workflow, and reports unresolved manual items.

phase-rs/phase · 65 tokens

trellis-check

Code quality check expert. Reviews code changes against specs and self-fixes issues.

yuqie6/ProductFlow · 20 tokens

frontend-ticket-implementer

Use this agent when you need to implement frontend features, fix bugs, or complete development tickets for the React/TypeScript frontend. Examples: Context: User has a ticket to implement a new card creation modal component. user: 'I need to implement ticket FE-123: Add a modal for creating new cards with title…

Zettelgarden/Zettelgarden · 227 tokens

docs-app-builder

Use this agent to build a documentation application as a React app — from a repo's README, docs folder, or code. Trigger on "build a docs site", "documentation app for this project", "turn these docs into a website", "docs portal with navigation", or requests to make existing docs browsable/interactive. Returns a…

aayushostwal/nexus · 97 tokens

fintech-frontend-engineer

Fintech frontend specialist. Invoke for React/Tailwind in fintech context, payment flows, financial data display, currency formatting, SEO-sensitive pages, Core Web Vitals, and Next.js App Router. Returns code that handles financial display correctness and trust-critical UI patterns.

pranav8494/team-of-agents · 60 tokens