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Found 10 Skills
Ask Gemini via the local `gemini` CLI (no MCP). Use when the user says "ask gemini" / "use gemini", wants a second opinion, needs large-context `@path` analysis, sandbox runs, or structured change-mode edits.
Operate the Clerk CLI (`clerk` binary) for authentication, user/org/session management, deploy verification, instance config, env keys, and any Clerk Backend or Platform API call. Use when the user mentions Clerk management tasks, "list clerk users", "create a clerk user", "update organization", "pull clerk config", "clerk env pull", "clerk doctor", "clerk deploy", "clerk deploy status", "clerk api", or any ad-hoc Clerk API request. Prefer the CLI over raw HTTP: it handles auth, key resolution, app/instance targeting, and formatting automatically.
Run commands in an isolated Linux microVM sandbox using the shuru CLI. Use when the user asks to execute untrusted code, install packages safely, test in a clean environment, or needs Linux-specific tooling on macOS.
TensorLake SDK for building agentic workflows, sandboxed code execution, and document parsing/extraction. Use when the user mentions tensorlake, or asks about TensorLake APIs/docs/capabilities. Also use when the user is building AI agents or agentic applications that need serverless workflow orchestration (parallel map/reduce DAGs), sandboxed execution of LLM-generated code, or document parsing, structured extraction, and OCR from PDFs/images. Works with any LLM provider (OpenAI, Anthropic), agent framework (LangChain, CrewAI, LlamaIndex), database, or API as the infrastructure layer.
Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges
Use when the user wants to use Google Gemini for analysis, large files or codebases, sandbox execution, or brainstorming. Uses headless Gemini CLI scripts (no MCP). Triggers on "use Gemini", "analyze with Gemini", "large file", "sandbox", "brainstorm with Gemini".
Deploy and configure OpenClaw AI bot gateway with Chinese IM platforms (Feishu, DingTalk, QQ, WeChat Work) using Docker
VM0 API for running AI agents in secure sandboxes. Use this skill to execute agents, manage runs, and download outputs (artifacts) and inputs (volumes) via the VM0 platform API.
Expert backend for run-os / run-os-sandboxed execution via x07-os-runner. Prefer `x07 run --profile os` / `x07 run --profile sandbox`.
Use when a task needs connected MCP servers, external services, dynamic MCP tool discovery, schema inspection, sandboxed MCP execution, or routing across many possible MCP tools.