multi-tenant-isolation
Enables multi-tenant isolation for AI agent swarms, ensuring strict data separation, process isolation, and secure resource management between deployments.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
522 skills found
Enables multi-tenant isolation for AI agent swarms, ensuring strict data separation, process isolation, and secure resource management between deployments.
Execute implementation plans in small, verifiable batches with pause-for-feedback checkpoints to prevent drift and ensure code quality.
Perform rigorous code reviews for FastMCP projects, focusing on API design, dependency management, and codebase consistency.
Build production-grade AI agents using LangGraph, Anthropic/OpenAI/vLLM, and structured outputs. Features streaming, A2A protocol, Pydantic validation, vector memory, and guardrails for resilient, multi-agent workflows.
Integrate Snowflake with MCP clients. Manage Snowflake endpoints, validate connectivity, and leverage Cortex AI (Search, Analyst, Agent) services directly within your AI workflow.
Automatically apply safe quality fixes including formatting (Black, isort), linting (Ruff auto-fixes), and resolving formatter conflicts to maintain Python code quality.
A specialized skill for surgical code refactoring. Improves maintainability, reduces technical debt, and applies design patterns without altering external behavior.
Generate hierarchical, AI-optimized documentation structures (AGENTS.md, agent.d) to streamline codebase context, setup, and navigation for AI coding assistants and developers.
Compiler-accurate semantic code analysis via LSP. Navigate definitions, references, and implementations, perform workspace-wide renames, and get file outlines for Python, Rust, Go, TypeScript/JS, and Java.
Audit UI code for Web Interface Guidelines compliance. Automatically checks accessibility, design standards, and UX best practices.
A Notion-based tracking system for tweet performance to enable data-driven content experimentation using reinforcement learning principles.
The final execution agent for the vibe-coding workflow. Builds your MVP incrementally by following the AGENTS.md master plan, managing session continuity, and verifying each feature via testing.