Data & ML

Calculate and model paid-media financial metrics including CPA, CPL, CPC, CPM, ROAS, MER, break-even targets, contribution margin, LTV:CAC, impression-share opportunity, budgets, forecasts, and experiment economics.

Provides persistent, compounding memory for AI agents across sessions using local markdown files, with optional Supabase-backed semantic search.

Selects the right Gemma model for a task, recommends deployment tooling (Gradio, Transformers.js, Vertex AI, MLX), and applies optimizations like MTP and QAT.

End-to-end Kaggle competition workflow for scored submissions, covering code competitions, validation, metrics, public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling, multi-notebook architectures, Kaggle GPU offload, and hidden-test debugging.

Defines the caption model (drop/rail/embed) and overlay law for compositing captions on top of video, never reserving a bottom band.

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.

Diagnoses business models using dontbesilent's ontological framework, offering consultation mode to dissolve problems and checkup mode to analyze business structures.

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.

Converts CSV, Excel, or JSON data into a polished, interactive visual report page with KPI cards, charts, data tables, and insights.

Generates OMG-compliant BPMN 2.0 XML and SVG diagrams from natural language process descriptions, with validation, automatic layout, and optional process optimization advisories.

Documents the design system of BMW's corporate website, including color palette, typography, spacing, and layout tokens for UI implementation.

Queries weather data, radar imagery, model maps, and meteorological calculations using 12 specialized tools.

Fine-tune Gemma models locally using QLoRA, Unsloth, or TRL for SFT, DPO, and reward modeling, with dataset preparation and conversion to GGUF or LiteRT-LM.

Generates a single-page team management dashboard with tabs for members, details, and activity log, including charts and CSV export.

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

Documents the warm, editorial design system of Claude.com, including color palette, typography, spacing, and surface modes for consistent brand implementation.

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.

Documents Ferrari's brand design system including color palette, typography, spacing, and layout tokens for use in marketing materials.

Connects MCP-compatible coding agents to Writingmate for model discovery, text comparison, image generation, and video generation using models like Seedance, Sora, Veo, Kling, and PixVerse.

Analyzes MiniMax's design system, documenting its dual identity of stark monochrome marketing and vibrant gradient product cards, with detailed color, typography, and layout tokens.

Operates Redpanda's Agentic Data Plane: manages AI agents, MCP servers, LLM providers, budgets, guardrails, and Cedar access policies via the `rpk ai` CLI and API, including OAuth wiring and spend/transcript insights.

Generates Mermaid architecture diagrams from a codebase, including C4 context and container diagrams, sequence diagrams for key flows, ER diagrams from database schemas, and module dependency graphs.

Optimize SQL queries, design database schemas, and tune performance across cloud-native and hybrid OLTP/OLAP environments.

Creates executable Polars dataframe contracts using Pandera's Polars backend for runtime validation of schemas, columns, and checks.

Write, review, debug, test, or optimize Python code using PyArrow arrays, schemas, tables, compute kernels, datasets, Parquet, and Arrow IPC.

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

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.

Builds Retrieval-Augmented Generation systems with document chunking, embedding generation, vector storage, and retrieval pipelines, including evaluation and optimization.