AI & ML

Build and deploy machine learning models with TensorFlow, covering Keras, data pipelines, and production serving.

Provides best practices for using MariaDB's built-in vector support for AI workloads, including SQL syntax for vector columns, indexes, distance functions, and RAG patterns.

Programmatically access Google NotebookLM via reverse-engineered RPC calls, managing notebooks, adding sources, querying, and generating or downloading artifacts like audio, video, quizzes, and slide decks.

Create new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, or build a new skill.

Runs independent AI CLI reviewers over phase plans and merges their feedback into a REVIEWS.md file.

Ingest, index, search, edit, and generate video and audio assets from files, URLs, RTSP feeds, or desktop capture, with real-time alerts and stream links.

Builds a scheduled, AI-powered data collection agent that scrapes public sources, enriches results with Gemini Flash, and stores them in Notion, Sheets, or Supabase.

Ingests video and audio from files, URLs, live feeds, or desktop capture; indexes and searches moments with timestamps; transcodes, edits timelines, generates media assets, and emits real-time alerts.

Generates, remixes, and manages short video clips via OpenAI's Sora API for cinematic shots, b-roll, and rapid concept iteration.

Builds an evidence-backed ECC install plan for a repository by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes.

Builds persistent multi-agent workflows on Claude Code using a kernel config, specialist agents, slash commands, file-based memory, and scheduled automation without external databases.

Performs neural web, code, company, and people searches through the Exa MCP server, with guidance on tool usage and parameters.

Generates images with Google Gemini's image generation API for UI mockups, icons, illustrations, and visual assets.

Generates images, videos, and audio using fal.ai models via MCP, covering text-to-image, text/image-to-video, text-to-speech, and video-to-audio.

Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Measures whether coding agents actually follow skills, rules, or agent definitions by generating test scenarios, running agents, and classifying tool calls to report compliance rates.

Composes ad-hoc teams of AI agents from local markdown personas and dispatches them in parallel on a task, then synthesizes their outputs.

Emulates Andrew Ng's teaching style to explain AI and machine learning concepts with structured, practical guidance.

Embody David Hume's empiricist and skeptical method to analyze causal claims, inductive arguments, moral reasoning, and metaphysical concepts.

Creates agent company packages conforming to the Agent Companies specification, either from scratch or by wrapping an existing repository.

Orchestrates multi-agent project builds with persistent state, parallel execution, and atomic git commits.

Runs a local voice MCP server in Rust for text-to-speech and speech-to-text, with build, test, and configuration guidance.

Builds and debugs n8n workflows, covering nodes, RAG with vector stores, the REST API, Code node scripts, expressions, and Docker hosting.

Sets up Claude Code for a project by analyzing the tech stack, installing relevant skills from skills.sh, generating custom skills, and configuring MCP servers.

Provides guidance on using JAX for machine learning and mathematical analysis, covering core concepts, transformations, ML specifics, control flow, and parallelism.

Routes prompts to any LLM model across multiple providers via CLI tools or APIs, with auto-discovery of new models and benchmark data.

Implements Manifold-Constrained Hyper-Connections (mHC) using Doubly Stochastic Matrices to improve deep learning stability.

Analyzes recent conversation messages to identify a supporter personality type and generate a shareable identity card with tool recommendations.

Discovers, installs, and manages AI agent skills from agentskill.sh, including searching, installing mid-session, scanning for security issues, and providing feedback.

Install, configure, and manage MCP servers through the mcpmu CLI, including registration with Claude Code, namespaces, permissions, and serve mode.

Spawns GLM-5 powered teammates with native thinking mode for coding, review, testing, planning, and research tasks.

Orchestrates multi-agent workflows defined in YAML piece files, delegating tasks to team members and managing state transitions.

Provides foundational infrastructure for the agent ecosystem, including entity memory management, model routing, and integration with the 1ai-skills hook system.

Creates and manages AI agent teams for complex engineering tasks, with model routing, cost optimization, and performance evaluation.

Writes documentation optimized for AI agent consumption, including SKILL.md, README, and API docs, using layered context hierarchies and RAG-friendly formatting.

Provides isolated, agent-native sandboxes for code execution, live preview URLs, browser automation, and access to 50+ tools via CLI or HTTP, with no SDK or API keys required.