discord-ops
Automate Discord server operations including message management, channel organization, and role assignments via MCP.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
206 skills found
Automate Discord server operations including message management, channel organization, and role assignments via MCP.
Development guide for lemline-core, the stateless Serverless Workflow engine. Manage workflow execution, node navigation, state transitions, JQ expression evaluation, error handling, and parallel fork logic.
Search and discover Claude Code skills and MCP servers from marketplaces, GitHub repositories, and registries to enhance your AI-assisted development workflow.
An automated memory middleware for AI agents, implementing a Retrieve-Respond-Save loop to maintain long-term persistent context across conversations.
Captures session learnings into Reusable Intelligence Infrastructure (RII). Converts one-time bug fixes and pattern discoveries into permanent agent-executable knowledge to prevent recurrence and accelerate future development.
Framework for multi-agent collaboration using the Google A2A protocol. Enables messaging, task delegation, and cross-agent coordination for CLI-based AI tools.
CLI interface for Gemini AI, enabling one-shot model inference, text generation, and JSON-formatted data extraction for OpenClaw users.
Advanced context engineering system for orchestrating AI agents, memory management, and token optimization to improve long-term persistence and project intelligence.
Systematic Kubernetes troubleshooting, pod diagnostics, cluster health monitoring, and incident response playbooks.
Expert SQL agent for modern database systems, query optimization, HTAP environments, and data architecture patterns. Optimize performance, schema design, and analytical workloads effectively.
Comprehensive AI-generated text detection framework. Features multi-layer analysis of vocabulary, structural patterns, model-specific fingerprints, and technical metadata artifacts to identify AI authorship.
A rigorous, four-phase methodology to enforce systematic root cause analysis before applying any code fixes.