tavily-web
Advanced web search, content extraction, and site crawling capabilities using the Tavily API, optimized for AI agent research and data gathering.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
421 skills found
Advanced web search, content extraction, and site crawling capabilities using the Tavily API, optimized for AI agent research and data gathering.
Streamline technical documentation by generating, updating, and refining README files. Tailors content for specific audiences including OSS contributors, internal teams, and personal projects.
Transforms content to match specific voice profiles, tones, or styles using configurable YAML templates for consistent brand and narrative output.
An automated memory middleware for AI agents, implementing a Retrieve-Respond-Save loop to maintain long-term persistent context across conversations.
A comprehensive security auditing and hardening assistant that applies best practices for authentication, input validation, secrets management, and SQL injection prevention to your codebase.
Guidance for Model Context Protocol (MCP) server development, including tool design, resource handling, and AI/ML integration patterns.
Generate, validate, and refine Mermaid diagrams including flowcharts, sequence diagrams, ERDs, and architecture maps to visualize complex software systems and workflows.
Create publication-quality plots and visualizations using matplotlib and seaborn. Works locally with any LLM.
A framework for crafting suspense, detective, and mystery narratives, emphasizing fair play principles, clue placement, and plot structure.
Pre-execution security guardrails for AI agents. Validates shell commands and file reads against 400+ security patterns to block destructive operations, credential theft, and unauthorized system access.
A microworld operating system for LLM-based agent living memory, transforming filesystems into navigable rooms and code into habitable worlds.
A framework to transform experimental ML prototypes into robust, production-ready Python packages using src layout, hybrid architecture, and strict configuration management.