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Found 4,989 Skills
Create accurate Japanese UI DESIGN.md files for AI agents with proper CJK typography, font stacks, line-height, kinsoku shori, and mixed typesetting rules.
Guidance for creating, running, fixing, and promoting behavioral evaluations. Use when verifying agent decision logic, debugging failures, debugging prompt steering, or adding workspace regression tests.
Retrieve time-windowed RSS evidence from SQLite and let the agent produce final summaries using RAG over selected records and fields. Use when generating daily, weekly, monthly, or custom-range AI tech digests directly in agent responses instead of fixed template reports.
Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.
Give an AI agent an encrypted inbox with the masumi-agent-messenger CLI. Use when agents need to message other agents, read durable inboxes, manage threads, coordinate async multi-agent workflows, request human approval, or automate inbox operations with JSON output.
Command-line interface for AdGuard Home - Network-wide ad blocking and DNS management via AdGuard Home REST API. Designed for AI agents and power users who need to manage filtering, DNS rewrites, clients, DHCP, and query logs without a GUI.
Create, optimize, and iteratively refine agent prompts and system prompts. Use when asked to "improve a prompt", "optimize a system prompt", "rewrite an agent prompt", "tune prompt wording", "make this prompt more reliable", or "adapt a prompt for OpenAI, Claude, or Gemini". Handles model-specific prompt guidance, prompt markers/tags, eval design, and meta optimization loops for new and existing prompts.
Creates and orchestrates multi-agent pipelines on the iii engine. Use when building AI agent collaboration, agent orchestration, research/review/synthesis chains, or any system where specialized agents hand off work through queues and shared state.
Comprehensive guide to why and how AI agents should use email. Use when evaluating whether an agent needs email, comparing email infrastructure options (AgentMail vs Gmail API vs Resend vs SendGrid vs SES), understanding security risks like prompt injection via email and OAuth credential exposure, or exploring common agent email use cases such as customer support agents, sales outreach, verification flows, and browser automation.
Architecture patterns and best practices for giving AI agents email capabilities. Use when designing how agents send, receive, and manage email conversations, building two-way communication loops, implementing human-in-the-loop approval with drafts, choosing between WebSockets and webhooks, setting up multi-agent email topologies, handling OTP and verification flows, or securing agent email against prompt injection.
Comprehensive guide to the AgentMail Python and TypeScript SDKs. Use when building AI agents that need their own email inboxes, sending or receiving emails programmatically, managing threads and conversations, handling attachments, creating drafts for human-in-the-loop approval, setting up real-time notifications via webhooks or WebSockets, configuring custom domains, managing allow/block lists, using pods for multi-tenant isolation, or integrating email into any AI agent workflow. Covers the full AgentMail API with code examples, best practices, and production patterns.
Audit all installed agent skills across global and project scopes to find and remove duplicate skills. Use when asked to audit my skills, deduplicate skills, clean up skills, or find duplicate skill installations. Don't use for creating or improving a single skill, running skill evals, or packaging/publishing skills.