47 boosters for "authentication" — open source, verified from GitHub, ready to install
A specialized agent for building enterprise-grade integrations on the Feishu (Lark) platform, including bots, workflows, and SSO authentication. Ideal for developers automating team collaboration and business processes within Feishu ecosystems.
Designs identity, authentication, and trust verification systems for autonomous AI agents in multi-agent environments, enabling agents to prove their identity, authorization, and audit trails. Ideal for developers building secure, accountable agent systems.
This booster helps developers build, review, and architect ASP.NET Core web applications by providing guidance aligned with current Microsoft best practices. It's essential for teams working with Blazor, Razor Pages, APIs, and other ASP.NET Core patterns.
Train language models using TRL (Transformer Reinforcement Learning) on fully managed Hugging Face infrastructure. No local GPU setup required—models train on cloud GPUs and results are automatically saved to the Hugging Face Hub. Use this skill when users want to: Use Unsloth () instead of standard
Run any workload on fully managed Hugging Face infrastructure. No local setup required—jobs run on cloud CPUs, GPUs, or TPUs and can persist results to the Hugging Face Hub. Use this skill when users want to: When assisting with jobs:
Provides the Hugging Face Hub CLI (`hf`) tool for downloading, uploading, and managing models, datasets, and Spaces directly from Claude Code. Essential for developers integrating Hugging Face resources into AI workflows.
This skill enables users to run Python workloads, Docker jobs, and GPU-intensive tasks on Hugging Face's managed infrastructure without local setup. It's valuable for ML engineers, data scientists, and developers needing cloud compute for training, inference, and batch processing.
A skill for fine-tuning and training language models on Hugging Face's cloud GPU infrastructure using TRL, supporting SFT, DPO, GRPO methods and GGUF conversion for local deployment. Developers and ML engineers working with cloud-based model training benefit from this comprehensive guidance.
Enables developers to interact with Hugging Face Hub directly from Claude Code using the `hf` CLI—downloading models/datasets, uploading files, creating repositories, and managing cache without leaving the coding environment.
Connect a Kubernetes cluster (EKS, GKE, AKS, or KOPS) to CAST AI for cost optimization, autoscaling, and security scanning. Covers API key generation, Helm chart installation of the CAST AI agent, and Terraform provider setup. Log in to https://console.cast.ai and navigate to API > API Access Keys.
Agent Toolkit MCP Server enables AI agents to integrate Clerk authentication into applications across multiple frameworks (Next.js, Express, React, etc.). Developers building AI-powered apps that need secure user authentication and session management benefit most from this toolkit.
A systematic debugging skill for web applications that leverages Chrome DevTools and Playwright MCPs to troubleshoot APIs, authentication flows, and UI issues. Developers working with web apps will benefit from its structured debugging approach and intelligent context discovery.
A Cursor rules booster that guides AI to prefer Bun as the default runtime and build tool over Node.js, npm, and other alternatives, with specific API recommendations. Developers using Bun in their projects benefit from consistent AI suggestions aligned with their tooling preferences.
This skill provides comprehensive guidance for all aspects of Playwright test development, from writing new tests to debugging and maintaining existing test suites. Consult these references based on what you're doing:
This skill enables developers to manage Azure DevOps resources (repos, pipelines, boards, work items) directly from the command line using the az CLI. It's essential for teams using Azure DevOps who want to automate workflows and integrate DevOps operations into CI/CD scripts.
Analyze, review, and provide recommendations for distributed system designs. Use when: (1) Reviewing existing system architectures for gaps or improvements, (2) Analyzing system designs for scalability, reliability, or performance issues, (3) Providing recommendations on load balancing, caching, databases, sharding, replication, messaging, rate limiting, authentication, resilience, or monitoring, (4) Assessing trade-offs in system design decisions, (5) Creating system design review documents with gaps and recommendations. Triggers: "review my system design", "analyze this architecture", "what are the gaps", "system design recommendations", "scalability review", "reliability analysis".
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
Transform a Vibes app into a multi-tenant SaaS with subdomain-based tenancy. Adds Clerk authentication, subscription gating, and generates a unified app with landing page, tenant routing, and admin dashboard.
Mazeway provides cursor-integrated authentication rules for building secure auth systems in Next.js projects using Supabase, emphasizing best practices for 2FA and device trust without external auth libraries.
Mazeway provides Cursor-specific rules for implementing authentication and authorization patterns in Next.js projects using Supabase, enabling developers to own their auth logic instead of relying on external packages. Ideal for developers building secure, self-contained authentication systems.
Mazeway provides Cursor-native rules for implementing authentication and authorization in Next.js projects using Supabase, enabling developers to own their auth logic rather than relying on external packages. Ideal for developers building secure, self-contained authentication systems.
Mazeway provides cursor-native rules for building authentication systems in Next.js with Supabase while keeping auth logic in your own codebase. Developers building secure, self-owned authentication layers benefit from these opinionated architectural patterns.
Generate text files and export to PNG/SVG/PDF using (local) or Kroki API (no install). 1. Check deps — try , fallback to Kroki if unavailable 2. Pick diagram type — choose from table below
Reference documentation for embedding Prismatic's integration marketplace and workflow builder inside a customer-facing web application. Embedding Prismatic means your customers never leave your app to manage integrations. The flow is: 1. Your backend generates a short-lived signed JWT (10 min) auth
