63 boosters for "configuration" — open source, verified from GitHub, ready to install
// Awesome CursorRules // A curated list of awesome .cursorrules files for enhancing Cursor AI experience // General guidelines
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.
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:
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.
You are the ZCF Template Engine Specialist for the ZCF (Zero-Config Code Flow) project.
You are the ZCF Configuration Architect for the ZCF (Zero-Config Code Flow) project.
.env files built for sharing powered by @env-spec decorator comments
Retrieve current documentation and code examples for any library using the Context7 CLI. Make sure the CLI is up to date before running commands: Or run directly without installing:
Checks Claude Octopus setup status and provides configuration instructions for missing dependencies like Codex CLI. Useful for developers setting up AI coding environments, though references appear outdated.
"$schema": "https://anthropic.com/claude-code/marketplace.schema.json", "name": "claude-health", "description": "Configuration health audit skill for Claude Code. Audits CLAUDE.md, rules, skills, hooks, subagents, and verifiers with bounded data collection.",
All canonicalized to via : A workspace can belong to multiple groups. Glob patterns matched via . into a workspace dir → vlt auto-targets that workspace for install/run/etc. For linked folders ( protocol), the folder must already be in the dependency chain for / to work.
Frontmatter fields above are primarily for Claude Code / OpenClaw. author: Agents365-ai category: Content Creation
Thin wrapper skills are the standard pattern for workflow skills. They: 2. Prepare delegation context 3. Invoke a subagent via Task tool
A specialized development agent for IOTA SDK that guides developers through implementing features across domain logic, persistence, migrations, templates, and configuration while maintaining DDD principles and multi-tenant isolation. Ideal for backend engineers building complex Go applications with structured architectural patterns.
This booster provides expert guidance for developing, debugging, and optimizing Azure AI Document Intelligence applications, covering architecture, security, best practices, and deployment patterns. Developers building document processing solutions on Azure will benefit from its comprehensive troubleshooting and design pattern knowledge.
Use this skill whenever the user wants to: This skill is organized to match the Rspack official documentation structure (https://rspack.rs/zh/guide/start/introduction, https://rspack.rs/zh/config/, https://rspack.rs/zh/plugins/, https://rspack.rs/zh/api/). When working with Rspack: 1. Identify the t
Lint agent configurations before they break your workflow. Validates Skills, Hooks, MCP, Memory, Plugins across Claude Code, Cursor, GitHub Copilot, and Codex CLI. Invoke when user asks to: If not found, install:
This skill transforms Claude into an interactive assistant for capturing and analyzing Claude Code's API communications using mitmproxy, a free, open-source HTTPS proxy tool. The skill supports three equally important use cases: 1. Learning & Exploration - Understanding Claude Code's internal workin
This skill generates reusable Relay-based Nodes components that: Activate this skill when users ask to: The skill automatically determines:
A practical guide for deploying serverless Python applications on Modal, enabling developers to run GPU-accelerated AI/ML workloads, web APIs, and batch jobs with minimal infrastructure configuration.
A practical guide to Supervised Fine-Tuning using SFTTrainer and Unsloth optimizations, enabling developers to efficiently adapt pre-trained LLMs for instruction-following with 2x faster training. Ideal for ML engineers building custom instruction-tuned models and reasoning systems.
You are helping the user configure their deployment so works automatically. Your job is to detect the deploy platform, production URL, health checks, and deploy status commands — then persist everything to CLAUDE.md.
<projectdescription> </projectdescription> <architecture_overview>
