AI & ML

Set up GPU profiling, tracing, and monitoring for inference workloads using vLLM, SGLang, PyTorch, and dstack services via the Graphsignal Profiler sidecar.

Install a local rebuttal workspace for academic papers with structured intake, reviewer analysis, and strategy planning to produce venue-compliant author responses.

Generate or edit Xiaohongshu (RedNote) cover images using GPT Image 2 / Codex, with a Gemini CLI fallback, supporting 18 preset styles and custom style learning.

Delegates tasks to specialized AI agents running in parallel via the Box0 platform, enabling code review, security checks, research, and documentation.

润色中文学术论文，识别并替换模板化、机械化的AI表达，使文本更自然、更符合人类学者的写作习惯。

Expert guidance for architecting, developing, and operating SurrealDB 3, covering SurrealQL, multi-model data modeling, vector search, security, deployment, performance tuning, SDK integration, and ecosystem tools.

Provides a persistent, queryable virtual filesystem backed by SurrealDB for AI agents, with a Rust core and a Python agent interface.

Connects AI agents to SurrealDB via built-in MCP (SurrealDB 3.1+) or standalone surrealmcp for database operations.

Find authoritative guidance for installing, configuring, operating, securing, and troubleshooting OpenClaw, including channels, model providers, Gateway operations, tools, plugins, automation, nodes, multi-agent routing, and CLI errors. Use for any question or maintenance task involving an OpenClaw installation.

Search and browse Civitai models, images, and videos; extract generation prompts; and get download commands for LoRAs and checkpoints.

Guides designing Dify workflows, covering node types, design patterns, templates, and best practices.

Optimizes Dify workflows and plugins by restructuring graphs, reducing LLM token usage, tuning worker pools, and improving parallel processing.

Integrates Dify with external systems via REST APIs, webhooks, and the MCP protocol, including client and server implementations.

Quick reference for the Agent Farm CLI, covering tower, dashboard, builder management, and configuration commands.

Covers AI, machine learning, LLMs, prompt engineering, and blockchain development with code examples and best practices for building AI applications and smart contracts.

Guides machine learning development with experiment tracking, hyperparameter optimization, model registry, and MLOps pipeline integration.

Installs and configures ktx, the open-source context layer for data agents, including database connections, embeddings, agent integration, and context ingestion.

Provides guidelines for building with Botpress's Agent Development Kit (ADK), covering primitives, project structure, CLI usage, and documentation lookups.

Annotates single-cell RNA-seq data by scoring marker genes, transferring labels with CellTypist, or reasoning over marker lists with an LLM.

Short alias that routes invocations to the vc-phase-loop skill for hands-off completion.

Quantize large language models to 4-bit precision using activation-aware weight quantization, reducing memory footprint and speeding up inference with minimal accuracy loss.

Classifies HTML pages, forms, and fields using machine learning to detect page types, form types, and field types from HTML content or URLs.

Generate images, videos, audio, and more using fal.ai AI models, with support for text-to-image, image-to-video, text-to-speech, speech-to-text, image editing, upscaling, model search, workflow creation, and cost estimation.

Quantize large language models to 8/4/3/2/1-bit precision without calibration data, using multiple optimized backends and integrations with HuggingFace Transformers, vLLM, and PEFT/LoRA.

High-performance numerical computing with JAX, covering functional transformations, Flax NNX, and best practices for ML research.

Scales Python ML workloads across clusters using Ray's distributed tasks, actors, data, and serving capabilities.

Annotates single-cell RNA-seq data by scoring marker genes, transferring labels with CellTypist, or reasoning over cluster markers with an LLM.

Fine-tune instruction-following LLMs with Unsloth's optimized SFTTrainer, covering dataset formatting, chat templates, training configuration, and thinking-model patterns.

Scaffolds a coder-eval task suite in a repository by scanning for testable components, writing one real task, and validating it.

Mines SpecStory coding histories from any agent into a persistent corpus, surfaces reproducible workflows with corroborated evidence, and interactively forges chosen ones into skills installed across agent harnesses.

Generate A2UI 0.8 protocol compliant UI code for agent-driven interfaces, including JSONL messages for surface updates, data model updates, and rendering.

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

Adds a persistent pattern or rule that Ralph will remember and apply to future stories.

Manages personal local Agent Skill files by detecting reusable material, searching for similar skills, and creating or updating SKILL.md folders after user approval.

Guides the creation of high-quality MCP servers that let LLMs interact with external services through well-designed tools, covering planning, implementation, testing, and evaluation.

Simulates an AI-assisted physician that combines modern AI tools with traditional methods to identify the most likely causes of a patient's symptoms.