Browse skills

Simulates RL environments using UV Miles data for robust agent training and improved performance in realistic scenarios.

Provides LLMs guidance and assistance for building AI and machine learning applications.

Molty-Assistant's memory agent stores, retrieves, and summarizes past conversations for context and improved future interactions.

Build custom LangChain agents with pre-configured tools and memory for complex task automation.

Designs and optimizes complex multi-agent systems using advanced reinforcement learning and emergent behavior strategies.

Suggests relevant industry experts and resources based on your project's needs, powered by CNN data.

Creates detailed markdown files describing PC-style agents, including stats, abilities, and background stories.

This skill template streamlines agent creation by providing a structured VCR-style approach for building consistent and effective conversational flows.

Analyzes code for bugs, vulnerabilities, and style issues using advanced static analysis techniques.

The Slop Analyzer identifies vague, rambling, or nonsensical text, helping you refine communication and ensure clarity.

Identifies potential conflicts and synergies between multiple active agents to optimize team performance.

This tool analyzes API calls to estimate token costs, helping developers optimize usage and manage expenses effectively.

Helps with data transformation, code generation, image processing as part of agent workflows workflows.

Automatically creates comprehensive documentation for your agent's functionality, inputs, outputs, and usage based on code and prompts.

Helps with code generation, image processing as part of agent workflows workflows.

Generates new AI agent skills based on provided descriptions, expanding capabilities and automating development workflows.

Kyldvs's create-subagents generates specialized AI assistants to tackle complex tasks through automated delegation and coordination.

Automates secure container deployments across environments, enforcing policies and minimizing vulnerabilities through automated checks.

Safely reverts deployments orchestrated by manastalukdar agents to a previous stable version, minimizing disruption.

Automates coordinated release deployments across multiple environments using a swarm of agents, minimizing downtime and risk.

Automates software release deployments across ruvnet infrastructure, minimizing errors and accelerating delivery cycles.

Proactively detects and alerts on infrastructure anomalies, performance degradation, and security threats in real-time.

Automatically detects, diagnoses, and corrects common errors in agent execution to maintain task progress.

This tool identifies recurring error patterns in logs to pinpoint root causes and accelerate debugging efforts for improved system reliability.