Loading...
Loading...
Found 1,684 Skills
NEAR AI agent development and integration. Use when building AI agents on NEAR, integrating AI models, creating agent workflows, or implementing AI-powered dApps on NEAR Protocol.
A meta skill that teaches AI agents how to discover, install, and use skills from the findskill.md ecosystem. Use when you need to extend capabilities by finding specialized skills, when a user asks to perform tasks that would benefit from specialized skills, or when explicitly asked to find or install skills.
Guidelines for creating AI agent skills. Use when writing new skills, documenting coding patterns, or reviewing skill files. Triggers when creating or modifying files in the skills/ directory.
Switch model profile for kata agents (quality/balanced/budget). Triggers include "set profile", "set profile".
Comprehensive knowledge of Claude Agent SDK architecture, tools, hooks, skills, and production patterns. Auto-activates for agent building, SDK integration, tool design, and MCP server tasks.
Use this skill when working with scientific research tools and workflows across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery. This skill provides access to 600+ scientific tools including machine learning models, datasets, APIs, and analysis packages. Use when searching for scientific tools, executing computational biology workflows, composing multi-step research pipelines, accessing databases like OpenTargets/PubChem/UniProt/PDB/ChEMBL, performing tool discovery for research tasks, or integrating scientific computational resources into LLM workflows.
Requirements Discovery Specification, applicable to exploratory scenarios, helps users identify high-ROI functional directions when they are confused through role-playing. Automatically triggered, purely conversational inspiration.
Workflow Checkpoint Basic Capabilities (Focus on Save and Resume): Record checkpoint progress and resume context in GitHub Issues. Applicable to any workflow stage, supporting automatic triggering and high-frequency manual calls. Keywords: save, resume, checkpoint, issue.
Amazon Bedrock AgentCore Memory for persistent agent knowledge across sessions. Episodic memory for learning from interactions, short-term for session context. Use when building agents that remember user preferences, learn from conversations, or maintain context across sessions.
Analyze footnotes and accounting policies from SEC filings using Octagon MCP. Use when researching revenue recognition policies, critical estimates, lease obligations, pension assumptions, stock compensation, contingencies, and new accounting pronouncements.
Letta framework for building stateful AI agents with long-term memory. Use for AI agent development, memory management, tool integration, and multi-agent systems.
Creates Cursor-specific AI subagents with isolated context for complex multi-step workflows. Use when creating subagents for Cursor editor specifically, following Cursor's patterns and directories (.cursor/agents/). Triggers on "cursor subagent", "cursor agent".