PixiJS v8 — fast 2D WebGL/WebGPU renderer. Use when building interactive graphics, games, or data visualizations in the browser. Covers Application setup, scene graph, sprites, graphics, text, and asset loading.

PixiJS — fast, lightweight 2D rendering library for the web.

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Query Google Trends data via SerpApi for search trend analysis, keyword discovery, topic comparison, and geographic interest patterns. Use when users need trending keyword data, want to compare search terms, or need Google Trends insights for content planning.

ALWAYS LOADED. Intelligent skill search router. When no installed skill matches the user's request, or when the user explicitly asks to find/search for a skill, run: skrt query '<user request>'. Read the top result's SKILL.md and follow its instructions. 智能技能路由器，当找不到匹配技能时自动搜索。触发词: find skill, search skill, 查找技能, 搜索技能, skillmux, skrt.

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Protect email pipelines from injection attacks, phishing, content manipulation, and AI agent exploitation. Use when building inbound email processing, sanitizing email content, detecting phishing or BEC, securing AI agents that read email, or hardening email infrastructure against spoofing and data exfiltration.

Receive, parse, and process incoming email via provider webhooks. Use when setting up inbound email handling, parsing MIME messages, extracting content from replies, detecting threads, filtering spam on inbound, or routing incoming messages.

Build dashboards, alerts, and monitoring systems for email sending operations. Use when setting up deliverability monitoring, configuring alert thresholds, checking blocklists, building email metrics dashboards, or responding to deliverability incidents.

Interactive conversation to understand the mathematical background and context of a problem. Use when user has a vague idea, intuition, or half-formed thought and needs to articulate it precisely.

Scans a whole project (JS/TS, Python, shell, Ruby/Go/PHP, Dockerfiles, YAML, package.json, and JS/TS tooling configs) for supply-chain and infostealer patterns — obfuscated JavaScript, `eval(atob())` / `new Function()` loaders, `createRequire` ESM escapes, browser & SSH & cloud credential theft (Chrome Safe Storage, Login Data, AWS keys, GitHub tokens, crypto wallets, PEM blocks), reverse shells and `curl | sh` droppers, persistence via `.bashrc` / `authorized_keys` / crontab / LaunchAgents, network exfiltration channels (Telegram bots, Discord/Slack webhooks, ngrok/transfer.sh), crypto miners, and suspicious `package.json` install hooks. Use when the user mentions suspicious config changes, unexplained build hangs, keychain/password prompts during `npm run dev` / `npm run build`, recent commits from unknown contributors, incident response, supply-chain attack, malware, infostealer, or when auditing a repo after a `git pull`.

Integrated analysis of expression, mutation, copy number, and methylation data from TCGA and GEO for solid tumor characterization.

Create data-rich, interactive HTML presentations with charts, architecture diagrams, code highlighting, and professional styling. Use when the user wants to build a presentation with data visualization, technical diagrams, metrics dashboards, or code examples. Supports Chart.js, ECharts, D3, CSS/HTML diagrams, inline SVG, Prism.js code highlighting, and 6 curated style presets.

Write clear, developer-first copy for Zed — leading with facts, grounded in craft.

Bypass Cloudflare and anti-bot protections using headless Chrome. When a URL is blocked, don't retry with HTTP clients — launch a real browser.

Manages Anki flashcards via AnkiConnect - adds flashcards from CSV files, searches existing flashcards, and updates card content. Use when working with Anki flashcards, CSV imports, spaced repetition, or when user mentions Anki, flashcards, or flashcard management.

looker-studio

This skill is for *using* a Looker Studio dashboard through the CLI — extracting values, understanding its pages and filters, exporting data, and exploring how numbers change under different filter co

The goal is to catch drift between what the dashboard displays and what the source workbook actually contains, both in the default view and under each filter.

Build and query AI-powered knowledge bases from claude-mem observations.

Decompose complex tasks, design dependency graphs, and coordinate multi-agent work with proper task descriptions and workload balancing. Use this skill when breaking down work for agent teams, managing task dependencies, or monitoring team progress.

Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.

Build automated billing systems for recurring payments, invoicing, subscription lifecycle, and dunning management. Use when implementing subscription billing, automating invoicing, or managing recurring payment systems.

Master defensive Bash programming techniques for production-grade scripts. Use when writing robust shell scripts, CI/CD pipelines, or system utilities requiring fault tolerance and safety.

Step-by-step cookbook for setting up cryptographically signed audit trails on Claude Code tool calls. Use when explaining, evaluating, or demonstrating the pattern before committing to the protect-mcp runtime hooks. Covers Cedar policy, Ed25519 receipts, offline verification, tamper detection, CI/CD integration, and SLSA composition.

Build scalable design systems with design tokens, theming infrastructure, and component architecture patterns. Use when creating design tokens, implementing theme switching, building component libraries, or establishing design system foundations.

Install the claw CLI tool — run NanoClaw agent containers from the command line without opening a chat app.

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

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.

Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.

Cloud computing platform for running Python on GPUs and serverless infrastructure. Use when deploying AI/ML models, running GPU-accelerated workloads, serving web endpoints, scheduling batch jobs, or scaling Python code to the cloud. Use this skill whenever the user mentions Modal, serverless GPU compute, deploying ML models to the cloud, serving inference endpoints, running batch processing in the cloud, or needs to scale Python workloads beyond their local machine. Also use when the user wants to run code on H100s, A100s, or other cloud GPUs, or needs to create a web API for a model.

Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

Query the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biological data including genes, drugs, diseases, phenotypes, and more.

Interact with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.

Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.

Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.

Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.

Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.

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.

Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.

Guide for building Graph Neural Networks with PyTorch Geometric (PyG). Use this skill whenever the user asks about graph neural networks, GNNs, node classification, link prediction, graph classification, message passing networks, heterogeneous graphs, neighbor sampling, or any task involving torch_geometric / PyG. Also trigger when you see imports from torch_geometric, or the user mentions graph convolutions (GCN, GAT, GraphSAGE, GIN), graph data structures, or working with relational/network data. Even if the user just says 'graph learning' or 'geometric deep learning', use this skill.

UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.

Query the U.S. Treasury Fiscal Data API for federal financial data including national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Access 54 datasets and 182 data tables with no API key required. Use when working with U.S. federal fiscal data, national debt tracking (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates on Treasury securities, foreign exchange rates, savings bonds, or any U.S. government financial statistics.

Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.

Converts X content to markdown:

Transform content into professional slide deck images. The deck is designed for **reading and sharing** (self-explanatory slides, logical scroll flow, social-media-friendly) rather than live presentat