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Cloud Backtest for Heavy Trading Jobs

trader-cloud-backtest

This skill dispatches computationally intensive quantitative trading jobs (such as multi-year walk-forward analysis, large Monte-Carlo simulations, parameter sweeping, or deep model training) to a managed cloud agent runtime. It is designed for large-scale, production-grade backtesting that exceeds local machine capacity, ensuring robust execution and artifact management via Anthropic's cloud services.

AAMAS Conference Submission Workflow

brycewang-stanford/Awesome-Journal-Skills

A comprehensive project management guide for submitting academic papers to the AAMAS conference. It details all critical milestones, including venue fit, evidence locking, abstract submission, double-blind review, rebuttal, and final camera-ready preparation. Essential for managing complex research involving game theory and multi-agent systems.

OpenViking Context Database Operator Skill

openviking-context-database

volcengine/OpenViking

This operator skill provides comprehensive control over the OpenViking context engine, enabling agents to manage long-term memory, session archives, and external resources within OpenClaw. It facilitates semantic recall, context querying, resource import, and recall trace debugging by communicating with a remote OpenViking server. Use this plugin when your agent requires advanced, persistent context management.

OpenViking Skills Management

volcengine/OpenViking

Manage OpenViking agent skills via the ov skills CLI: install from local directories or Git sources, list, search, show, update, remove, and validate SKILL.md formats.

Advanced Filesystem Management Tool

opensquilla/opensquilla

A comprehensive skill for AI agents to perform advanced filesystem operations. It provides features for intelligent file listing with deep filtering, powerful content and pattern searching, safe batch file copying, and detailed directory analysis (statistics, tree visualization). Ideal for code analysis, system auditing, and managing project assets.

Ouroboros Configuration Management

ouroboros-config

This skill manages the Ouroboros AI framework configuration. It allows users to open the settings GUI via browser or TUI, or configure settings conversationally. Users can edit runtime choices, model selections, and LLM backends. It supports local and remote server modes, enabling customization of agents and execution profiles through ouroboros config commands.

AI Agent Memory Management MCP

agent-memory-mcp

sickn33/agentic-awesome-skills

This MCP server provides a persistent and searchable memory bank for AI agents. It enables reading, writing, and searching long-term knowledge regarding architecture, patterns, and decisions. It automatically syncs with project documentation and includes a standalone dashboard for visualization. Requires Node.js setup for local deployment.

Multi-Agent System Optimization

agent-orchestration-multi-agent-optimize

sickn33/agentic-awesome-skills

Optimize multi-agent systems through coordinated profiling, workload distribution, and cost-aware orchestration. This skill helps improve agent performance, throughput, and reliability by identifying bottlenecks in workflows. It covers context window optimization, parallel execution strategies, and cost management for LLM usage. Suitable for engineering complex AI workflows requiring high efficiency and stability.

AI Agent Orchestrator

agent-orchestrator

sickn33/agentic-awesome-skills

This meta-skill orchestrates all agents within the ecosystem, providing automatic skill scanning, capability matching, multi-skill workflow coordination, and registry management. It helps manage complex tasks by coordinating multiple AI tools without executing them directly, ensuring efficient resource allocation and task planning.

AI Agents Architect

ai-agents-architect

sickn33/agentic-awesome-skills

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Ensures graceful degradation and clear failure modes. Capable of agent architecture design, tool calling, memory management, and complex task decomposition. Includes knowledge of ReAct loops, Plan-and-Execute patterns, and safety guardrails.

AWS Bedrock AgentCore Expert

sickn33/agentic-awesome-skills

Comprehensive expert for deploying and managing AI agents at scale using AWS Bedrock AgentCore. Covers all nine core services including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, and Evaluations. Use for agent deployment, MCP integration, credential management, and cross-service workflows with AWS CLI.

Azure AI Agents Persistent SDK

azure-ai-agents-persistent-dotnet

sickn33/agentic-awesome-skills

This low-level SDK enables .NET developers to create and manage persistent AI agents on Azure. It supports threads, messages, runs, and tools integration. Includes features for function calling, vector store management, and file search. Ideal for building complex AI applications with C# and Azure services.

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