ML Ops
Machine learning operations
ai-sdk-agents
by BjornMelin
Expert guidance for building AI agents with ToolLoopAgent (AI SDK v6+). Use when creating agents, configuring stopWhen/prepareStep, callOptionsSchema/prepareCall, dynamic tool selection, tool loops, or agent workflows (sequential, routing, evaluator-optimizer, orchestrator-worker). Triggers: ToolLoopAgent, agent loop, stopWhen, stepCountIs, prepareStep, callOptionsSchema, prepareCall, hasToolCall, InferAgentUIMessage, agent workflows.
pipeline-metrics
by OmniNode-ai
Report pipeline health metrics — rework ratio, cycle time, CI stability, and feature velocity
notebook-ml-architect
by BjornMelin
Expert guidance for auditing, refactoring, and designing machine learning Jupyter notebooks with production-quality patterns. Use when: (1) Analyzing notebook structure and identifying anti-patterns, (2) Detecting data leakage and reproducibility issues, (3) Refactoring messy notebooks into modular pipelines, (4) Generating templates for ML workflows (EDA, classification, experiments), (5) Adding reproducibility instrumentation (seeding, logging, env capture), (6) Converting notebooks to Python scripts, (7) Generating experiment summary reports. Triggers on: ML notebook, Jupyter audit, notebook refactor, data leakage, experiment template, ipynb best practices, notebook to script, reproducibility.
crash-recovery
by OmniNode-ai
Show recent pipeline state to orient after an unexpected session end or crash
swiftui-view-refactor
by pondorasti
Refactor and review SwiftUI view files for consistent structure, dependency injection, and Observation usage. Use when asked to clean up a SwiftUI view's layout/ordering, handle view models safely (non-optional when possible), or standardize how dependencies and @Observable state are initialized and passed.
content-modeling-best-practices
by display-design-studio
Structured content modeling principles with Sanity-specific guidance. Use when designing or reviewing content schemas, document types, field structures, or content architecture — including decisions around references vs embedding, content reuse, taxonomy, page builders, multi-channel delivery, or refactoring existing schemas. Trigger when the user mentions schema design, content model, document types, content structure, headless CMS architecture, or asks how to model any content type.
everclaw
by profbernardoj
Open-source first AI inference — GLM-5 as default, Claude as fallback only. Own your inference forever via the Morpheus decentralized network. Stake MOR tokens, access GLM-5, GLM-4.7 Flash, Kimi K2.5, and 30+ models with persistent inference by recycling staked MOR. Open-source first model router routes all tiers to Morpheus by default — Claude only kicks in as an escape hatch when needed. Includes Morpheus API Gateway bootstrap for zero-config startup, OpenAI-compatible proxy with auto-session management, automatic retry with fresh sessions, OpenAI-compatible error classification to prevent cooldown cascades, multi-key auth rotation v2 with proactive DIEM balance monitoring and reactive 402 watchdog, Gateway Guardian v5 with direct curl inference probes (eliminates Signal spam), proactive Venice DIEM credit monitoring, circuit breaker for stuck sub-agents, nuclear self-healing restart, always-on proxy-router with launchd auto-restart, smart session archiver, three-shift cyclic execution engine (v2 with 15-minute execution loops), 24/7 always-on power configuration for macOS, bundled security skills, zero-dependency wallet management via macOS Keychain, x402 payment client for agent-to-agent USDC payments, and ERC-8004 agent registry reader for discovering trustless agents on Base.
executing-plans
by OmniNode-ai
Use when partner provides a complete implementation plan to execute — reviews the plan critically, verifies live PR state against plan assumptions, creates Linear tickets via plan-to-tickets, then routes to epic-team (≥3 tickets) or ticket-pipeline (1-2 tickets)
scanpy
by tondevrel
Scalable toolkit for analyzing single-cell gene expression data. Built on top of Anndata, focusing on clustering, trajectory inference, and visualization.
pytorch-deployment
by tondevrel
Advanced sub-skill for PyTorch focused on model productionization and deployment. Covers TorchScript (JIT/Tracing), ONNX export, LibTorch (C++ API), and inference optimization (Quantization, Pruning).
pytorch-research
by tondevrel
Advanced sub-skill for PyTorch focused on deep research and production engineering. Covers custom Autograd functions, module hooks, advanced initialization, Distributed Data Parallel (DDP), and performance profiling.
Model Patterns
by Kaakati
"Entity and model patterns with JSON serialization, immutability, and equality"
photutils
by tondevrel
An Astropy coordinated package for detecting and performing photometry of astronomical sources. Provides tools for background estimation, source detection (DAOFIND, IRAF), aperture photometry, and PSF (Point Spread Function) fitting. Use when working with astronomical image analysis, star/galaxy detection, measuring brightness (photometry), background subtraction, PSF fitting, aperture photometry, centroiding, or isophotal analysis.
cobrapy
by tondevrel
Constraints-Based Reconstruction and Analysis for Python. Used for modeling large-scale metabolic networks in microorganisms.
Repository Patterns
by Kaakati
"Repository interface and implementation patterns with offline-first strategies"
pyomo
by tondevrel
Python Optimization Modeling Objects. A high-level framework for formulating, solving, and analyzing optimization models. Supports Linear Programming (LP), Mixed-Integer Linear Programming (MILP), and Non-Linear Programming (NLP). Part of the COIN-OR project. Use for mathematical optimization, linear programming, mixed-integer programming, non-linear programming, strategic planning, process engineering, energy systems, supply chain optimization, stochastic programming, and solver integration with IPOPT, SCIP, Gurobi, CPLEX, or GLPK.
fastapi-streamlit
by tondevrel
Dual skill for deploying scientific models. FastAPI provides a high-performance, asynchronous web framework for building APIs with automatic documentation. Streamlit enables rapid creation of interactive data applications and dashboards directly from Python scripts. Load when working with web APIs, model serving, REST endpoints, interactive dashboards, data visualization UIs, scientific app deployment, async web frameworks, Pydantic validation, uvicorn, or building production-ready scientific tools.
Error Handling Patterns
by Kaakati
"Exception classes, failure classes, Either type, and error handling strategies"
endurance-coach
by shiv19
Create personalized triathlon, marathon, and ultra-endurance training plans. Use when athletes ask for training plans, workout schedules, race preparation, or coaching advice. Can sync with Strava to analyze training history, or work from manually provided fitness data. Generates periodized plans with sport-specific workouts, zones, and race-day strategies.
ActiveRecord Query Patterns
by Kaakati
"Complete guide to ActiveRecord query optimization, associations, scopes, and PostgreSQL-specific patterns. Use this skill when writing database queries, designing model associations, creating migrations, optimizing query performance, or debugging N+1 queries and grouping errors."
pytorch
by tondevrel
Leading deep learning framework. Provides Tensors and Dynamic Computational Graphs with strong GPU acceleration. Widely used for research, neural networks, and differentiable programming.
magento-model-developer
by maxnorm
Designs and implements data layer architecture for Magento 2. Use when creating data models, designing database schemas, implementing repositories, or working with EAV/flat table structures. Masters entity design, repository patterns, collections, and database optimization.
ortools
by tondevrel
Google Optimization Tools. An open-source software suite for optimization, specialized in vehicle routing, flows, integer and linear programming, and constraint programming. Features the world-class CP-SAT solver. Use for vehicle routing problems (VRP), scheduling, bin packing, knapsack problems, linear programming (LP), integer programming (MIP), network flows, constraint programming, combinatorial optimization, resource allocation, shift scheduling, job-shop scheduling, and discrete optimization problems.
nuxt-enums
by leeovery
TypeScript enum pattern with Castable interface for model integration. Use when creating enums with behavior methods (colors, labels), defining fixed value sets, or integrating enums with the model casting system.