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clerk-performance-tuning

A model-agnostic agent-skills platform.

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项目 README

来源文件:README.md

抓取于 2026年8月28日

Tons of Skills

A model-agnostic agent-skills platform. The canonical layer is harness-free by construction; Claude Code is currently the verified-native harness. Other harnesses remain engineering candidates until their native-path integration is verified; source research alone is never presented as public support.

Release CLI Plugins Skills GitHub Stars skills.sh Sponsor: Kobiton Buy me a monster

ko-fi

Version semantics: the release badge is this marketplace's display version. npm packages, including the ccpi CLI and publishable plugins, retain their own package versions; they are intentionally not expected to equal the display version. The version-surface checker governs the display surfaces without rewriting package semver.

Install

Inside Claude Code, one command installs the whole marketplace:

/plugin marketplace add jeremylongshore/claude-code-plugins

Or use the CLI:

pnpm add -g @intentsolutionsio/ccpi
ccpi install devops-automation-pack

Browse the marketplace · Explore plugins · Download bundles

Killer Skill of the Week — no-ai-slop by Peter Yang

Strip AI slop from any draft — named-pattern edits that keep the writer's real voice

no-ai-slop does two jobs and refuses to fake a third. In Edit mode it makes the minimum effective edit — cutting throat-clearing, weak verbs, and abstract nouns while deliberately preserving the writer's cadence, bluntness, humor, and honest admissions, so a rough draft still sounds like the same person afterward. In Detect mode it names each AI-slop pattern it finds, quotes the offending line, and gives the fix in a few words — and pointedly does NOT score the draft or guess whether an AI wrote it. That restraint is the whole point: AI detectors guess; named patterns are evidence the reader can check. MIT-licensed, single focused skill, actively maintained by Peter Yang.

"AI detectors guess. Named patterns are evidence the user can check." — Peter Yang

Grade: A | Week of July 22, 2026 (W30) | View on GitHub

Previous picks: tonone, mnemos, databricks-pack, kobiton-automate, skyvern, code-cleanup, web-analytics, token-optimizer, executive-assistant-skills, skill-creator, cursor-pack, crypto-portfolio-tracker. See all at tonsofskills.com.

Scale, labeled

Every number below names the cohort it counts and the command that reproduces it — an unlabeled count is how a corpus ends up with five contradictory answers to "how many skills."

CountCohortReproduce with
442catalog plugins (catalog-entry cohort)node scripts/generate-readme-toc.mjs over marketplace.extended.json
3,067marketplace-visible skills (distinct)node -e "import('./scripts/corpus-resolver.mjs').then(m=>console.log(m.resolveCorpus('marketplace-visible').length))"
347agent definitions in pluginsgit ls-files 'plugins/**' | grep '/agents/.*\.md'
19plugin categoriesls -d plugins/*/

📦 Live npm Downloads

Across 396 published packages in the claude-code-plugins namespace. Updated daily by GitHub Actions.

WindowAll packagesEstablished (>30d)
Last 24 hours962962
Last 7 days2,9202,916
Last 30 days12,86812,779

"Established" excludes packages first published within the last 30 days, so a bulk-publish event doesn't dominate the headline.

Top 10 by last 30 days:

#PackageLast 30d
1@intentsolutionsio/openrouter-pack556
2@intentsolutionsio/groq-pack496
3@intentsolutionsio/databricks-pack274
4@intentsolutionsio/clickhouse-pack273
5@intentsolutionsio/wallet-security-auditor263
6@intentsolutionsio/notion-pack258
7@intentsolutionsio/elevenlabs-pack244
8@intentsolutionsio/freshie-inventory-manager214
9@intentsolutionsio/supabase-pack210
10@intentsolutionsio/agency-os204

Last refreshed 2026-08-19T03:03:05.709Z.

Ways in

Five real questions, five doors — each resolves to a live, generated surface, never a hand-maintained list:

Browse by category

The 19 categories below link into the live marketplace. Plugin counts are the catalog-entry cohort — regenerated from marketplace.extended.json by this generator; the catalog itself lives on tonsofskills.com, never in this file (§ 6A of the platform blueprint).

CategoryPlugins
🤖AI & Machine Learning36
🎭AI Agents & Agency10
🔌API Development26
💼Business Tools6
👥Community21
₿Crypto & Web327
💾Database26
🎨Design2
🔧DevOps & Infrastructure36
📚Examples & Templates5
🧩MCP Servers16
📦Packages5
⚡Performance25
✅Productivity30
🎁SaaS Skill Packs106
🔐Security27
✨Skill Enhancers9
🧪Testing28
📁Analytics1

What the classes mean

Four artifact classes live in this repository, distinguished on sight and never blurred — provenance is a truth requirement here, not a UX nicety:

ClassWhat it isHow the reader can tell
Canonical skillFirst-party, harness-free, the source of truthNo .source.json in its plugin directory
Generated adapterA thin, machine-produced harness projectionLives under a generated path with a "generated — do not edit" header
First-party packageAn Intent Solutions distribution (npm, cowork zip)@intentsolutionsio scope, IS-authored license
Upstream mirrorSomebody else's work, hosted mirror-by-default.source.json present — upstream author, license, and pinned commit recorded

Certification

Not yet certified. The certification program (tiers T0–T4 with retained, hash-matched evidence) is a later epic of the platform blueprint; until its report exists, no artifact on this surface claims a tier. This line is rendered from the absence of certification-report.json — honestly, not cosmetically.

Contribute

Start with the contribution guide, then the intake and review standards every submission passes through:

Governance

Provenance

External plugins are hosted mirror-by-default: the contributor's repository stays the source of truth, every mirrored source is pinned in a content lockfile, and upstream credit — author, license, resolved commit — is recorded in the mirror itself. Improvements flow by upstreaming to the author's repository, never by silently editing the mirror. The full decision record is the external-sync model.

License

MIT for the repository scaffolding and first-party tooling; each plugin carries its own license in its manifest, and mirrored plugins keep their upstream license verbatim.

其他

中风险

  • 来源需自行核对维护者身份。
  • 包含脚本或命令调用,安装前请复核。
  • 可能需要外部 token、网络权限或第三方服务。
  • 未检测到高风险命令。
  • 扫描发现:2 条。

Codex — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
  3. 将 "skills/.curated/clerk-performance-tuning" 文件夹复制到 Codex 的 skills 目录中。
  4. 重启 Codex 让新的 skill 生效。

Codex — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Codex 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Codex 让新的 skill 生效。

Claude Code — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
  3. 将 "skills/.curated/clerk-performance-tuning" 文件夹复制到 Claude Code 的 skills 目录中。
  4. 重启 Claude Code 让新的 skill 生效。

Claude Code — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Claude Code 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Claude Code 让新的 skill 生效。

Cursor — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
  3. 将 "skills/.curated/clerk-performance-tuning" 文件夹复制到 Cursor 的 skills 目录中。
  4. 重启 Cursor 让新的 skill 生效。

Cursor — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Cursor 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Cursor 让新的 skill 生效。

GitHub Copilot — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
  3. 将 "skills/.curated/clerk-performance-tuning" 文件夹复制到 GitHub Copilot 的 skills 目录中。
  4. 重启 GitHub Copilot 让新的 skill 生效。

GitHub Copilot — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 GitHub Copilot 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 GitHub Copilot 让新的 skill 生效。

Windsurf — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
  3. 将 "skills/.curated/clerk-performance-tuning" 文件夹复制到 Windsurf 的 skills 目录中。
  4. 重启 Windsurf 让新的 skill 生效。

Windsurf — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Windsurf 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Windsurf 让新的 skill 生效。
查看 SKILL.md 原文
name: clerk-performance-tuning
description: 'Optimize Clerk authentication performance.

  Use when improving auth response times, reducing latency,

  or optimizing Clerk SDK usage.

  Trigger with phrases like "clerk performance", "clerk optimization",

  "clerk slow", "clerk latency", "optimize clerk".

  '
allowed-tools: Read, Write, Edit, Grep
version: 1.14.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- clerk
- performance
- authentication
compatibility: Designed for Claude Code

Clerk Performance Tuning

Overview

Optimize Clerk authentication for best performance. Covers middleware optimization, user data caching, token handling, lazy loading, and edge runtime configuration.

Prerequisites

  • Clerk integration working
  • Performance monitoring in place (Lighthouse, Web Vitals)
  • Understanding of Next.js rendering strategies

Instructions

Step 1: Optimize Middleware (Skip Static Assets)

// middleware.ts — avoid running auth on static files
import { clerkMiddleware, createRouteMatcher } from '@clerk/nextjs/server'

const isPublicRoute = createRouteMatcher(['/', '/sign-in(.*)', '/sign-up(.*)', '/api/webhooks(.*)'])

export default clerkMiddleware(async (auth, req) => {
  if (!isPublicRoute(req)) {
    await auth.protect()
  }
})

// Restrict matcher to avoid processing static assets
export const config = {
  matcher: [
    // Skip _next, static files, and images
    '/((?!_next/static|_next/image|favicon.ico|.*\\.(?:svg|png|jpg|jpeg|gif|webp|ico)).*)',
    '/(api|trpc)(.*)',
  ],
}

Step 2: Cache User Data

// lib/cached-user.ts
import { auth, currentUser } from '@clerk/nextjs/server'
import { cache } from 'react'

// React cache: deduplicates within a single request
export const getAuthUser = cache(async () => {
  const { userId } = await auth()
  if (!userId) return null
  return currentUser()
})

// Usage in multiple server components (only one Clerk API call per request):
// const user = await getAuthUser()

For cross-request caching with unstable_cache:

import { unstable_cache } from 'next/cache'
import { clerkClient } from '@clerk/nextjs/server'

export const getCachedUserProfile = unstable_cache(
  async (userId: string) => {
    const client = await clerkClient()
    const user = await client.users.getUser(userId)
    return {
      id: user.id,
      name: `${user.firstName} ${user.lastName}`,
      email: user.emailAddresses[0]?.emailAddress,
      imageUrl: user.imageUrl,
    }
  },
  ['user-profile'],
  { revalidate: 300 } // Cache for 5 minutes
)

Step 3: Optimize Token Handling

// lib/token-cache.ts
let tokenCache: { token: string; expiresAt: number } | null = null

export async function getOptimizedToken(getToken: () => Promise<string | null>) {
  // Reuse token if it has more than 30 seconds remaining
  if (tokenCache && tokenCache.expiresAt > Date.now() + 30_000) {
    return tokenCache.token
  }

  const token = await getToken()
  if (token) {
    const payload = JSON.parse(atob(token.split('.')[1]))
    tokenCache = { token, expiresAt: payload.exp * 1000 }
  }

  return token
}

Step 4: Lazy Load Auth Components

// components/lazy-auth.tsx
'use client'
import dynamic from 'next/dynamic'

// Only load UserButton when needed (saves ~15KB)
const UserButton = dynamic(
  () => import('@clerk/nextjs').then((mod) => mod.UserButton),
  { ssr: false, loading: () => <div className="w-8 h-8 rounded-full bg-gray-200 animate-pulse" /> }
)

const SignInButton = dynamic(
  () => import('@clerk/nextjs').then((mod) => mod.SignInButton),
  { ssr: false }
)

export { UserButton, SignInButton }

Step 5: Optimize Server Components

// app/dashboard/page.tsx — parallel data fetching
import { auth } from '@clerk/nextjs/server'
import { Suspense } from 'react'

export default async function Dashboard() {
  const { userId } = await auth()
  if (!userId) return null

  return (
    <div>
      {/* Parallel loading with Suspense boundaries */}
      <Suspense fallback={<div>Loading profile...</div>}>
        <UserProfile userId={userId} />
      </Suspense>
      <Suspense fallback={<div>Loading activity...</div>}>
        <RecentActivity userId={userId} />
      </Suspense>
    </div>
  )
}

async function UserProfile({ userId }: { userId: string }) {
  const profile = await getCachedUserProfile(userId)
  return <div>{profile.name}</div>
}

async function RecentActivity({ userId }: { userId: string }) {
  const activity = await db.activity.findMany({ where: { userId }, take: 10 })
  return <ul>{activity.map((a) => <li key={a.id}>{a.description}</li>)}</ul>
}

Step 6: Edge Runtime for Middleware

// middleware.ts — runs on Vercel Edge (cold start <50ms vs ~250ms Node)
import { clerkMiddleware } from '@clerk/nextjs/server'

export default clerkMiddleware()

// Clerk middleware is Edge-compatible by default on Vercel
export const config = {
  matcher: ['/((?!_next/static|_next/image|favicon.ico).*)'],
  runtime: 'edge', // Explicitly opt into Edge Runtime
}

Output

  • Middleware skipping static assets (fewer auth checks)
  • React cache() deduplicating user fetches within requests
  • Cross-request user profile caching (5-minute TTL)
  • Lazy-loaded auth components reducing bundle size
  • Parallel Suspense boundaries for dashboard rendering
  • Edge Runtime middleware for faster cold starts

Error Handling

IssueCauseSolution
Slow initial page loadBlocking auth callsUse Suspense boundaries for parallel loading
High Clerk API latencyNo cachingUse cache() and unstable_cache()
Large JS bundleAll Clerk components loadedUse dynamic() imports for auth UI components
Slow middleware cold startNode.js runtimeSwitch to Edge Runtime on Vercel
Stale cached user dataCache not invalidatedInvalidate on user.updated webhook

Examples

Measure Clerk Auth Overhead

// lib/perf-measure.ts
export async function measureAuthTime() {
  const start = performance.now()
  const { userId } = await auth()
  const authMs = performance.now() - start
  console.log(`[Perf] auth() took ${authMs.toFixed(1)}ms, userId: ${userId}`)
  return { userId, authMs }
}

Resources

Next Steps

Proceed to clerk-cost-tuning for cost optimization strategies.

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