tzurot-council-mcp
Multi-perspective AI consultation for technical architecture, complex refactoring, and structured debugging.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
385 skills found
Multi-perspective AI consultation for technical architecture, complex refactoring, and structured debugging.
Persistent state management and workflow analytics using DuckDB for task dependency tracking, historical metrics, and context checkpointing.
Automates the generation of .http request files for Spring Boot REST controllers to simplify API documentation and testing.
CLI tools for Svelte 5 documentation lookup and code analysis. Automate Svelte component creation, debugging, and linting with real-time documentation retrieval and code autofixing.
Manage Python environments and packages using uv. Expert guidance for fast, modern project setup, dependency management, script execution, and tool installation as a drop-in replacement for pip, virtualenv, and poetry.
Automate Kubernetes GitOps workflows with ArgoCD, Helm, and Kustomize. Manage multi-environment deployments, infrastructure as code, and CI/CD pipelines efficiently.
Full-stack application orchestrator that analyzes natural language requests to determine tech stacks, scaffold projects, and coordinate specialized development agents.
An all-in-one Chinese daily utility toolkit: weather, currency exchange, news, and package tracking. Zero configuration, no API keys required.
A meta-skill for building robust AI agent skills using a TDD approach: define failure (RED), implement the skill (GREEN), and plug rationalization loopholes (REFACTOR).
Build modern, composable, and accessible React UI components following the components.build specification. Use for design systems, component libraries, and reusable UI architectures.
Systematic project technology stack detection, framework-specific skill auto-loading, and multi-stack analysis for fullstack projects like React + Go.
Foundational mental model and operational rules for using TraceMem to ensure secure, auditable, and compliant AI agent execution.