技能列表

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Text-To-Speech with MLX (Apple Silicon) and opensource models (default QWen3-TTS) locally.

Speech-To-Text with MLX (Apple Silicon) and opensource models (default GLM-ASR-Nano-2512) locally.

Deploy a lightweight status API that exposes your OpenClaw bot's runtime health, service connectivity, cron jobs, skills, system metrics, and more. Use when setting up a monitoring dashboard, health endpoint, or status page for an OpenClaw agent. Supports any services via config (HTTP checks, CLI commands, file checks). Zero dependencies — Node.js only.

Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Mlfinlab concepts, best practices, and implementation patterns.

Build, fill, stress-test, and iterate on a Business Model Canvas for a solopreneur. Use when designing or redesigning how a business creates, delivers, and captures value — covering all nine BMC blocks plus solopreneur-specific adaptations like the "Time & Energy" block and unit economics validation. Trigger on "business model canvas", "design my business model", "how will I make money", "business model", "BMC", "value proposition canvas", "how does my business work", "monetize my idea".

Visual analysis and diagnostic tools to help machine learning model selection. ml-visualizer, python, anaconda, estimator, machine-learning, matplotlib.

Job board for AI agents to hire humans for physical-world tasks.

Campaign link builder and pre-launch validator for AI agents. Build UTM-tracked links, validate destinations, and inspect landing pages for social sharing readiness (OG tags, Twitter Cards, viewport, canonical, favicons). The mlz preflight command does everything in one call and returns a go/no-go report.

Extract text and layout from images and PDFs using LLMWhisperer API. Good for handwriting and complex forms.

MiroMind Deep Research Skill - 使用 MiroThinker AI 进行深度研究。触发词：/miromind。当用户想对某个主题进行深度研究时使用。

Create documentation optimized for AI agent consumption. Use when writing SKILL.md files, README files, API docs, or any documentation that will be read by LLMs in context windows. Helps structure content for RAG retrieval, token efficiency, and the Hybrid Context Hierarchy.