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Found 1,463 Skills
Give first-time users a short, value-first Kitaru tour with the public returns-agent template. Use when someone has no agent or traces of their own, arrives from Kitaru onboarding, asks for a demo, tutorial, quickstart, or guided example, needs the public template cloned or prepared, wants the coding agent to prepare trace annotations before they judge sessions, or wants to experience Kitaru's value before learning the full investigation method. Prepare a three-session frontend review, let the human provide verdicts, turn one accepted finding into a deterministic evaluator, and finish with one approved bounded replay experiment. Route real agents, open-ended discovery, and production evidence to kitaru-investigation instead.
Advanced search options in GrepAI. Use this skill for JSON output, compact mode, and AI agent integration.
Give AI agents their own email inboxes using the AgentMail API. Use when building email agents, sending/receiving emails programmatically, managing inboxes, handling attachments, organizing with labels, creating drafts for human approval, or setting up real-time notifications via webhooks/websockets. Supports multi-tenant isolation with pods.
Research codebase comprehensively using parallel sub-agents to answer user questions. Use when the user asks to "research the codebase", "understand how X works", or "investigate Y".
View investment accounts, check portfolio performance, monitor 401k, and research funds on Fidelity
Amazon Bedrock AgentCore platform for building, deploying, and operating production AI agents. Covers Runtime, Gateway, Browser, Code Interpreter, and Identity services. Use when building Bedrock agents, deploying AI agents to production, or integrating with AgentCore services.
Ensure that all responses from the Agent in this project are in Chinese. When users have any conversations, code explanations, error prompts, or documentations with the Agent, the Agent should always respond in Chinese unless the user explicitly requests another language.
This skill helps users get started with existing (brownfield) projects by scanning the codebase, documenting structure and purpose, analyzing architecture and technical stack, identifying design flaws, suggesting improvements for testing and CI/CD pipelines, and generating AI agent constitution files (AGENTS.md) with project-specific context, coding principles, and UI/UX guidelines.
Before starting any significant task, force explicit evaluation of available skills. For each potentially relevant skill, state YES/NO with reasoning. Only proceed to implementation after skills have been consciously evaluated and activated. Prevents the ~50% "coin flip" activation rate that occurs when skills are passively available but not deliberately considered.
Developer oversight and AI agent coaching. Use when viewing project status across repos, syncing GitHub data, or analyzing agents.md against commit patterns.
Activates when the user asks about Agent Skills, wants to find reusable AI capabilities, needs to install skills, or mentions skills for Claude. Use for discovering, retrieving, and installing skills.
Audit existing skills (global and project-level) for agent-friendliness, consistency, and best practices. Use when asked to "audit my skills", "review skill setup", "analyze skill quality", "check skill health", "improve my skills", or when wanting an assessment of the overall skill ecosystem. Provides actionable recommendations for improving skill effectiveness.