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 agentmods add skills/benja-pauls/serpentstack/clerknpx skills add Benja-Pauls/SerpentStack --skill clerkgit clone --depth 1 https://github.com/Benja-Pauls/SerpentStackWrote 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/benja-pauls/serpentstack/clerk)<a href="https://agentmods.dev/skills/benja-pauls/serpentstack/clerk"><img src="https://agentmods.dev/badge/skills/benja-pauls/serpentstack/clerk.svg" alt="Measured on agentmods" 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 | $0.00059 | $0.00893 |
| Opus 5 | $0.00030 | $0.00447 |
| Sonnet 5 | $0.00012 | $0.00179 |
| Haiku 4.5 | $0.00006 | $0.00089 |
Grade A, and why
clerk 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clerk Skills Router
Version Detection
Check package.json to determine the Clerk SDK version. This determines which patterns to use:
| Package | Core 2 (LTS until Jan 2027) | Current |
|---|---|---|
@clerk/nextjs |
v5–v6 | v7+ |
@clerk/react or @clerk/clerk-react |
v5–v6 | v7+ |
@clerk/expo or @clerk/clerk-expo |
v1–v2 | v3+ |
@clerk/react-router |
v1–v2 | v3+ |
@clerk/tanstack-react-start |
< v0.26.0 | v0.26.0+ |
Default to current if the version is unclear or the project is new. Core 2 packages use @clerk/clerk-react and @clerk/clerk-expo (with clerk- prefix); current packages use @clerk/react and @clerk/expo.
All skills are written for the current SDK. When something differs in Core 2, it's noted inline with > **Core 2 ONLY (skip if current SDK):** callouts. The exception is clerk-custom-ui, which has separate core-2/ and core-3/ directories for custom flow hooks since those APIs are entirely different between versions.
By Task
Adding Clerk to your project → Use clerk-setup
- Framework detection and quickstart
- Environment setup, API keys, Keyless flow
- Migration from other auth providers
Custom sign-in/sign-up UI → Use clerk-custom-ui
- Custom authentication flows with
useSignIn/useSignUphooks - Appearance and styling (themes, colors, layout)
<Show>component for conditional rendering
Advanced Next.js patterns → Use clerk-nextjs-patterns
- Server vs Client auth APIs
- Middleware strategies
- Server Actions, caching
- API route protection
B2B / Organizations → Use clerk-orgs
- Multi-tenant apps
- Organization slugs in URLs
- Roles, permissions, RBAC
- Member management
Webhooks → Use clerk-webhooks
- Real-time events
- Data syncing
- Notifications & integrations
E2E Testing → Use clerk-testing
- Playwright/Cypress setup
- Auth flow testing
- Test utilities
Swift / native iOS auth → Use clerk-swift
- Native iOS Swift and SwiftUI projects
- ClerkKit and ClerkKitUI implementation guidance
- Source-driven patterns from
clerk-ios
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 · 90 lines · 59 tokens per session scan A acfa6c532bea
clerk is a skill published in the GitHub repository Benja-Pauls/SerpentStack (2 stars, last pushed 5mo ago), licensed MIT. It adds 59 tokens to every session and 893 once invoked, about $0.0003 per session on Opus 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…