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Found 1,152 Skills
Complete setup for automated agent-driven development. Define features as user stories with testable acceptance criteria, then run AI agents in a loop until all stories pass.
CloudBase Run backend development rules (Function mode/Container mode). Use this skill when deploying backend services that require long connections, multi-language support, custom environments, or AI agent development.
Build AI agents with structured access to Sanity content via Context MCP. Covers Studio setup, agent implementation, and advanced patterns like client-side tools and custom rendering.
Build and deploy AI agents with Cloudbase Agent (TypeScript), a TypeScript SDK implementing the AG-UI protocol. Use when: (1) deploying agent servers with @cloudbase/agent-server, (2) using LangGraph adapter with ClientStateAnnotation, (3) using LangChain adapter with clientTools(), (4) building custom adapters that implement AbstractAgent, (5) understanding AG-UI protocol events, (6) building web UI clients with @ag-ui/client, (7) building WeChat Mini Program UIs with @cloudbase/agent-ui-miniprogram.
Community incident reporting for AI agents. Contribute to collective security by reporting threats.
Choose and combine Eve storage primitives to give agents persistent memory — short-term workspace, medium-term attachments and threads, long-term org docs and filesystem. Use when designing how agents remember, retrieve, and share knowledge.
Dispatch background AI worker agents to execute tasks via checklist-based plans.
Create, improve, and test skills for the z-schema JSON Schema validator library. Use this skill whenever the user wants to create a new skill from scratch, turn a workflow into a reusable skill, update or refine an existing skill, write test cases for a skill, or organize reference material for a skill. Also use when someone mentions "skill", "SKILL.md", or wants to document a z-schema workflow for reuse by humans or AI agents.
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.
Interactive session to craft a system prompt for an AI agent powered by Sanity Agent Context MCP.
Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. This skill covers the Interactions API, the recommended way to use Gemini models and agents in Python and TypeScript.
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.