Top Agent Skills

Ruthless product and app critique for Nick's workflow. Use when evaluating an app, landing page, flow, or product experience to identify why users may bounce, distrust it, fail to activate, or never come back. Focus on practical weaknesses, not polite fluff.

Offer design and packaging for Nick's products and services. Use when shaping pricing, packages, guarantees, feature bundles, positioning, or making an offer more compelling and easier to buy.

Sales asset creation for Nick's products and client work. Use when creating one-pagers, product explainers, demo outlines, sales decks, or concise materials that help someone understand and buy quickly.

Local-first secret scanning for repos and git history. Use before every push, when scanning for exposed keys, checking for committed credentials, or auditing a repo for accidental secret leaks. Designed for Nick's workflow and safer than forcing suspicious marketplace secret scanners.

Launch planning and go-live operations for Nick's products. Use when preparing a product launch, shipping a new app, setting up a waitlist, planning post-launch steps, or making sure a built product is actually ready for users and growth.

Elite admin and internal-tool UX for Nick's apps. Use when designing dashboards, operator workflows, tables, filters, bulk actions, and information-dense interfaces that still feel fast, clear, and trustworthy.

API backend test generation for Nick's stack, especially Next.js App Router APIs with Supabase-aware auth assumptions. Use when testing backend routes, generating API test suites, validating authenticated vs unauthenticated access, checking malformed inputs, or building route-by-route backend coverage for projects that use /app/api or /pages/api.

Dependency auditing for Nick's projects with focus on Node and Python. Use before deploys, during maintenance, or when checking packages for vulnerabilities, outdated versions, license issues, and upgrade risk. Flags critical CVEs as deploy blockers and produces a prioritized upgrade plan.

Secure and powerful Playwright browser automation for testing websites, checking deploys, taking screenshots, filling forms, validating login flows, responsive QA, deploy QA, accessibility smoke checks, and browser-based verification. Use when Nick asks to test a page, verify a deployment, automate browser interactions, capture screenshots, inspect console errors, check mobile/desktop rendering, or run real Chromium-based browser checks.

Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.

Product strategy, market validation, commercial filtering, and MVP definition for Nick's workflow. Use when turning vague ideas into product plans, evaluating startup opportunities, identifying real market gaps, deciding if an idea should be killed before build, prioritizing features, shaping positioning, defining monetization, or judging whether a concept is strong enough to deserve design and engineering effort. Focus on painful problems, clear buyers, credible wedges, practical validation, and realistic paths to revenue.

Supabase-first reference and implementation skill for Nick's app stack. Use when writing Supabase queries, auth flows, RLS policies, storage rules, realtime features, edge-function integrations, migrations, or debugging Supabase behavior. Prefer this instead of guessing Supabase APIs or patterns. Bias toward product-led implementation choices, trust-aware access control, MVP discipline, and using only the Supabase features the product actually needs.

Generate professional UI designs using Google Stitch before building any frontend. Use this skill when building apps, websites, dashboards, landing pages, or any user-facing interface.

Practical codebase onboarding for Nick's workflow. Use when opening a stale project, picking up a new repo, rebuilding context after time away, or generating fast markdown docs that explain how to start working on a codebase right now. Focus on setup, key files, flows, commands, risks, and what to touch first.

When reviewing code, generate the complete corrected version — not just the issues, but the exact fixed code ready to copy-paste.

Onboarding and activation optimization for Nick's products. Use when improving first-run experience, reducing drop-off, guiding users to value faster, or cleaning up empty states, setup friction, and early confusion.

Top-layer project orchestration skill for Nick's workflow. Use when a request involves multiple stages, skills, or deliverables and the work needs to stay aligned from idea to scope to design to schema to build to QA to deploy. Coordinates the right sequence, enforces stage gates, prevents drift and overbuilding, tracks status/blockers/next actions, and creates clear handoffs between strategist, design, schema, Supabase, build, QA, and launch work.

Forge reviews its own skill updates, review history, and research outputs before publishing them.

React & Next.js — Forge Skill

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.

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.

TypeScript Patterns — Agent Arena

Capacity Planning — Real-Time Agent Workload Tracking

Database Review — Forge Skill

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.

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

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.

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

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.

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

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.

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

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

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.

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.

Comprehensive quantum computing toolkit for building, optimizing, and executing quantum circuits. Use when working with quantum algorithms, simulations, or quantum hardware including (1) Building quantum circuits with gates and measurements, (2) Running quantum algorithms (VQE, QAOA, Grover), (3) Transpiling/optimizing circuits for hardware, (4) Executing on IBM Quantum or other providers, (5) Quantum chemistry and materials science, (6) Quantum machine learning, (7) Visualizing circuits and results, or (8) Any quantum computing development task.

Single-cell RNA-seq analysis. Load .h5ad/10X data, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

Molecular machine learning toolkit. Property prediction (ADMET, toxicity), GNNs (GCN, MPNN), MoleculeNet benchmarks, pretrained models, featurization, for drug discovery ML.

Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.

Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).

Fetch up-to-date Railway documentation to answer questions accurately. Use when user asks about Railway features, how Railway works, or shares a docs.railway.com URL.

Extends pandas for geospatial vector data operations including reading/writing shapefiles, GeoJSON, and GeoPackage, performing spatial joins, coordinate transformations, and creating static or interactive maps.

Automated hypothesis generation and testing using large language models. Use this skill when generating scientific hypotheses from datasets, combining literature insights with empirical data, testing hypotheses against observational data, or conducting systematic hypothesis exploration for research discovery in domains like deception detection, AI content detection, mental health analysis, or other empirical research tasks.

Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.

Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.

Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.

Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates.

Phylogenetic tree toolkit (ETE). Tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy, visualization (PDF/SVG), for phylogenomics.

Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.

Foundational plotting library. Create line plots, scatter, bar, histograms, heatmaps, 3D, subplots, export PNG/PDF/SVG, for scientific visualization and publication figures.