Assess whether a dataset or data domain is ready for AI, analytics, or modeling before a project commits time and budget. Use when an agent needs a judgment-heavy data science workflow for score whether data is usable for ai work, including evidence review, local artifact inspection, risk classification…
Forge a coding or agentic prompt optimized for Claude Opus 4.7 or GPT-5.5 (Codex CLI) by interviewing the user with structured multiple-choice questions, then writing a precise XML-tagged prompt and optional SPEC.md handoff. Use whenever the user asks to write a prompt, scope a coding task, design a system prompt for…
Write optimized Triton GPU kernels for deep learning operations. Covers the full spectrum from basic vector ops to Flash Attention, persistent matmul, fused normalization, quantized GEMM, and memory-efficient patterns.
Evaluate RAG pipeline retrieval and generation quality separately. Measure Recall@k, Precision@k, MRR, NDCG@k for retrieval. Assess faithfulness and relevance for generation. Use when the AI feature uses retrieval (search, knowledge base, document QA). Do NOT use for non-RAG AI features.
An AI product planning guide for deciding whether to use retrieval-augmented generation (RAG) or an agent. RAG lets an AI search a knowledge collection before answering, while an agent can choose actions and tools.
Give text-only LLMs (DeepSeek, Xiaomi MiMo, GLM-4.5, MiniMax, Llama 3.x, etc.) eyes by analyzing images, screenshots, UI captures, diagrams, charts, and OCR documents through free multi-modal APIs with automatic engine fallback and caching. Images are handled by the browser-driven web engines FIRST (Doubao, Kimi…
An image-annotation workflow for creating COCO detection and instance-segmentation labels for selected object categories in one image. COCO is a common format for training and evaluating computer-vision models.
This skill should be used when the user asks to "implement a DiD regression", "run a staggered difference-in-differences", "set up an event study", "implement IV / 2SLS", "run a regression discontinuity design", "build synthetic control", "do propensity score matching", "test parallel trends", "run Honest DiD", "wild…
Overview of all available Pinecone skills and what a user needs to get started. Invoke when a user asks what skills are available, how to get started with Pinecone, or what they need to set up before using any Pinecone skill.
A practical extension layer for Guandata BI, a business-intelligence platform used to query data, build charts, and publish dashboards. It covers advanced data-pipeline work and custom HTML, CSS, and JavaScript dashboards beyond the standard tools.
Use s-gw when working with credentials, private keys, API tokens, SSH identities, browser credentials, or other sensitive data in agentic coding workflows. Prefer typed handles and local approved execution over exposing raw secret values to a model.
Select and connect the right vector-store backend for the vector-mcp MCP server — chromadb, postgres/pgvector, qdrant, couchbase, or mongodb — and supply the correct dbtype/connection parameters that every collection and search call needs. Use when the agent must decide which engine to target, wire up…
Geospatial Active Inference framework with 45 modules for ecological, civic, and commercial spatial analysis. Use when working with geospatial data, Active Inference, Bayesian modeling, H3 hexagonal indexing, spatial statistics, or any domain-specific geographic analysis (agriculture, health, economics, risk, climate…
You have access to Leeroopedia, a curated ML/AI knowledge base, via MCP tools. These are real MCP tools registered in your environment -- call them directly like any other tool. They contain framework-specific docs, code examples, API references, and best practices.
Package and deploy Databricks Asset Bundles with proper parameterization, multi-environment support, and serverless compute. Handles project structure, databricks.yml generation, validation, and deployment. Use when packaging tested code for production, deploying pipelines, or managing multi-environment deployments.
Use RoutIR — call a running endpoint with the client, stand up a local server that mixes locally-hosted services with services proxied from a remote master server, and extend RoutIR with new bi-encoders, rerankers, and document collections by writing a small config (and optionally one Python file referenced via…
Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and…
Use when Experiment must build, run, compare, or record reproducible ML/AI paper experiments locally or through the Research Assistant-configured ssh-bash tool and verified SSHFS workspace, including baselines, datasets, controlled trials, multi-seed formal evidence, ablations, and results promotion. Examples: user…
End-to-end ML toolkit with 26 CLI commands. Use when training models, tuning hyperparameters, detecting data drift, generating HTML reports with charts, profiling datasets, detecting anomalies, forecasting time series, checking fairness, or serving models as REST APIs. Prefer over raw sklearn when you need automated…
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: