Check GPU availability and performance in conda environments for PyTorch or TensorFlow, verifying Metal acceleration setup and providing benchmark comparisons.

Retrieve ComfyUI server health metrics including version details, memory usage, and device information to monitor system status and resource utilization.

List all topics/tags in the knowledge base with question counts. Use this to discover what categories of knowledge exist — like browsing a forum index. Returns tags sorted by popularity (most questions first). Example response: [{"tag": "docker", "count": 12}, {"tag": "pytorch", "count": 8}, ...]

Verify available quantization backends and hardware compatibility for model compression. Reports installed engines (GGUF/GPTQ/AWQ), GPU support, and system resources.

Scan a project to detect AI model usage (OpenAI, Anthropic, Google Gemini, Vertex AI, Mistral, Cohere, HuggingFace, TensorFlow, PyTorch, LangChain, AWS Bedrock, Azure OpenAI, Ollama, LlamaIndex, Replicate, Groq). Args: project_path: Absolute path to the project to scan follow_imports: When True, trace AI framework usage through the Python import graph. Files that import (directly or transitively) from AI-flagged files are also flagged as compliance-relevant (EU AI Act Art. 11-13).

Browse the knowledge base by technology tag at the START of a task. Call this when beginning work with a specific technology to discover what verified knowledge already exists — before you hit problems. Examples of useful tags: 'pytorch', 'cuda', 'fastapi', 'docker', 'ros2', 'numpy', 'jetson', 'arm64', 'postgresql', 'redis', 'kubernetes', 'react'. Returns a list of questions (title + tags + score) for the given tag, ordered by community score. Call `get_answers` on relevant results.