Latest Agent Skills

Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Genomic file toolkit. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, FASTA/FASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

List, switch, and configure Railway projects. Use when user wants to list all projects, switch projects, rename a project, enable/disable PR deploys, make a project public/private, or modify project settings.

Add official Railway database services (Postgres, Redis, MySQL, MongoDB). Use when user wants to add a database, says "add postgres", "add redis", "add database", "connect to database", or "wire up the database". For other templates (Ghost, Strapi, n8n), use the railway-templates skill.

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that don't fit in memory.

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.

CLI/Python toolkit for rapid bioinformatics queries. Preferred for quick BLAST searches. Access to 20+ databases: gene info (Ensembl/UniProt), AlphaFold, ARCHS4, Enrichr, OpenTargets, COSMIC, genome downloads. For advanced BLAST/batch processing, use biopython. For multi-database integration, use bioservices.

Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.

Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

Check service status, rename services, change service icons, link services, or create services with Docker images. For creating services with local code, prefer railway-new skill. For GitHub repo sources, use railway-new skill to create empty service then railway-environment skill to configure source.

Query resource usage metrics for Railway services. Use when user asks about resource usage, CPU, memory, network, disk, or service performance like "how much memory is my service using" or "is my service slow".

Best practices and comprehensive guide for Remotion - programmatic video creation in React with animations, compositions, and media handling

Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.

Check current Railway project status for this directory. Use when user asks "railway status", "is it running", "what's deployed", "deployment status", or about uptime. NOT for variables or configuration queries - use railway-environment skill for those.

Add, view, or remove domains for Railway services. Use when user wants to add a domain, generate a railway domain, check current domains, get the URL for a service, or remove a domain.

Deploy code to Railway using "railway up". Use when user wants to push code, says "railway up", "deploy", "ship", or "push". For initial setup or creating services, use railway-new skill. For Docker images, use railway-environment skill.

Remove AI-generated code slop from a branch. Use when cleaning up AI-generated code, removing unnecessary comments, defensive checks, or type casts. Checks diff against main and fixes style inconsistencies.

Create commit messages following Sentry conventions. Use when committing code changes, writing commit messages, or formatting git history. Follows conventional commits with Sentry-specific issue references.

Comprehensive guide for Manim Community - Python framework for creating mathematical animations and educational videos with programmatic control

Create Railway projects, services, and databases with proper configuration. Use when user says "setup", "deploy to railway", "initialize", "create project", "create service", or wants to deploy from GitHub. Handles initial setup AND adding services to existing projects. For databases, use railway-railway-database skill instead.

Database Review — Forge Skill

Protocol for monitoring repo changes and extracting new knowledge.

Token Standards

Foundry Testing & Toolchain

DeFi Primitives

How MaksPM hands off work to agents using sessions_spawn for continuous pipeline flow, with file-reference pattern for preserving full project specs. Updated 2026-03-21 with 9-phase pipeline and Forge architecture phase.

Capacity Planning — Real-Time Agent Workload Tracking

Stays current on UI design patterns, tools, and frameworks by monitoring release notes and running targeted search queries.

Test coverage and quality review — what needs tests, test quality assessment, anti-patterns, and the testing pyramid for Next.js + Supabase applications.

Forge Research — Forge Skill

Chainlink CCIP — Cross-Chain Interoperability Protocol

TypeScript Patterns — Agent Arena

Index of cloned framework repos for Maks's reference during builds.

Scout research skill — Market Sizing

Project Tracking — Structured Active Project Files

Automated visual design review — screenshot V0 demo URLs or local HTML, analyze rendered output, and validate against brand system. Works with both V0 live previews and Stitch-generated HTML.

SKILL — Stitch Mastery

SKILL — Design System

SKILL — Brand Systems

App Store Optimization for mobile launches (iOS App Store, Google Play). Use when preparing a mobile app launch, optimizing app store listings, planning screenshot sequences, writing app store copy, doing keyword research for app stores, planning preview videos, managing reviews, or A/B testing app store assets. Relevant for Expo/React Native apps going to stores. Not for web-only products.

Regex fluency — syntax, ReDoS prevention, production validation patterns, and regex code review checklist.

DevOps & Docker — Forge Skill

Web3 Frontend Integration

Vyper Mastery

Provides a comprehensive reference for the Move programming language, covering its resource-oriented philosophy, type system, abilities, and safety guarantees for Sui and Aptos blockchains.

Full automated QA suite — visual design review + UAT functional testing. Screenshots every viewport, analyzes against Nick's design system, then runs functional UAT (navigation, links, forms, buttons, auth flow, accessibility, performance, console errors, responsive testing). Use after every deployment.

Nick's enterprise design system. Enforces his visual standards on every web project — typography, color, layout, spacing, components, and anti-patterns. Must be referenced before any build spec is written. Produces "Enterprise Confidence with Clean Authority" — never generic AI design.

Identifies, assesses, and mitigates risks at every phase of a development pipeline.

SKILL — Color Theory

High-fidelity website/app clone design pipeline. Use when asked to clone, replicate, copy, or recreate any existing website or app screen. Captures real assets (images, SVGs, fonts, colors), extracts exact design tokens, generates the clone in Stitch, composites real assets into the output, then runs section-by-section visual comparison against the reference. Produces 90%+ accurate clones by combining Stitch generation with real asset injection.

React & Next.js — Forge Skill

Huff Language — EVM Bytecode Mastery

Supabase Realtime Patterns

Next.js App Router — Agent Arena Patterns