Skills directory · page 39

Use when a wrong answer is expensive: strategy research, comparing several products or markets, validating a hypothesis with outside data. Fans out searches and sub-agents, triangulates each claim across 3+ sources and saves every source with quotes. Quick facts: answer directly.

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.

Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan.

Expert in launching small, focused SaaS products fast - the indie hacker approach to building profitable software. Covers idea validation, MVP development, pricing, launch strategies, and growing to sustainable revenue. Ship in weeks, not months. Use when: micro saas, indie hacker, small saas, side project, saas mvp.

Master microservices architecture patterns including service boundaries, inter-service communication, data management, and resilience patterns for building distributed systems.

Microsoft Entra Authentication Events SDK for .NET. Azure Functions triggers for custom authentication extensions. Use for token enrichment, custom claims, attribute collection, and OTP customization in Entra ID. Triggers: "Authentication Events", "WebJobsAuthenticationEventsTrigger", "OnTokenIssuanceStart", "OnAttributeCollectionStart", "custom claims", "token enrichment", "Entra custom extension", "authentication extension".

Understand Microsoft technologies by querying official documentation. Use whenever the user asks how something works, wants tutorials, needs configuration options, limits, quotas, or best practices for any Microsoft technology (Azure, .NET, M365, Windows, Power Platform, etc.)—even if they don't mention "docs." If the question is about understanding a concept rather than writing code, this is the right skill.

Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent, managed harness agent, Copilot harness, voice agent, create/update/invoke/evaluate agent, add tool to agent, agent insights, batch/continuous eval, continuous monitoring, agent CI/CD, optimize/improve prompt, optimize agent instructions, Agent Optimizer, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).

Create, read, edit, and template Word, PowerPoint, and Excel files offline with small Python CLIs. Use for reports, letters, decks, workbooks, tracked changes, comments, and CSV conversion. Not for legacy binary formats (.doc/.ppt/.xls), ODF files, or WYSIWYG layout work.

Use when moving tests from Cypress or Selenium to Playwright ('migrate tests', 'convert tests', 'replace selenium').

Migrate test files from `as` type assertions to @total-typescript/shoehorn. Use when user mentions shoehorn, wants to replace `as` in tests, or needs partial test data.

Plan a migration with zero or minimal downtime: phased plan, compatibility check, rollback scripts, for schemas, databases and services. Load whenever the user must change a live table, move a database or cut over without downtime.

Write the least code: no over-engineering, fewer dependencies. Use whenever the user wants it simpler; applies a ladder first: YAGNI, reuse, stdlib, native platform, existing deps.

End-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codebases. Covers problem framing, data readiness, architectural decoupling, and baseline model integration. Use when adding a machine learning capability to a codebase that has none, from problem framing through a baseline model.

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.

Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.

Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.

Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.

Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform

Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform

Mobile-first design thinking and decision-making for iOS and Android apps. Touch interaction, performance patterns, platform conventions. Teaches principles, not fixed values. Use when building React Native, Flutter, or native mobile apps.

Mobile game development principles. Touch input, battery, performance, app stores.

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.

Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.

State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.

Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).

RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.

Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.

Establish or maintain a business module's local agent instructions, domain-context links, and interface ownership when implementing a new module or changing its responsibilities. Reuse project-level rules and existing ECC workflows; ordinary bug fixes, styling, and read-only design discussions do not start module documentation setup.

Govern cross-module regression in large repositories with a REGRESSION.md ledger that records each module's downstream consumers and executable acceptance command. After a change, run the changed module and every affected downstream command, and use observed exit codes as regression evidence under the project's delivery policy. Use for module regression, regression ledgers, impact audits, downstream verification, and changes where modifying A may break B.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Brainstorm 3-5 monetization strategies with audience fit, risks, and validation experiments. Use when exploring revenue models, evaluating pricing strategies, or deciding how to monetize a product.

Expert in monorepo architecture, build systems, and dependency management at scale. Masters Nx, Turborepo, Bazel, and Lerna for efficient multi-project development. Use PROACTIVELY for monorepo setup,

Use for Turborepo, Nx, pnpm-workspace or Lerna setup, affected-only builds, remote caching or a multi-repo to monorepo move. Maps packages and the dependency graph with monorepo_analyzer.py.

Use when running, planning or speeding up a month-end (or quarter-end) close — building or reviewing the close checklist and calendar, reconciling a bank statement or sub-ledger to the general ledger, writing or reviewing flux (variance) explanations, or finding why the close takes too many days. Orders close tasks by dependency and finds the critical path, proves each reconciliation and ages what is left, and refuses to sign off material fluctuations explained with boilerplate.

Create custom external web service APIs for Moodle LMS. Use when implementing web services for course management, user tracking, quiz operations, or custom plugin functionality. Covers parameter validation, database operations, error handling, service registration, and Moodle coding standards.

Advanced motion patterns for React / Next.js — drag & drop, gestures, text animations, SVG path drawing, custom hooks, imperative sequences (useAnimate), loaders, and the full API decision tree. Requires motion-foundations. Use when building drag and drop, gestures, text or SVG animation, or imperative animation sequences in React or Next.js.

Complete production-ready guide for Motion Canvas with ESM/CommonJS workarounds, full setup templates, and troubleshooting for programmatic video creation using TypeScript

Taste rules for Remotion motion graphics — timing, easing, springs, typography, color, texture, and scene continuity, with concrete numbers. Use whenever you create, animate, retime, or polish a video, composition, scene, or transition in this repo.

Code-only motion design pipeline (no After Effects) for Raphaël / Howseen: launch films, showreels, product promos, LinkedIn/X videos, meme clips. Use when asked to make a motion design video, a promo/launch film, a showreel, "remake this video", a video from a prompt (e.g. "make a 15s motion graphics video…"), to change a video's music/SFX, or to prepare memes for posts. Covers the brief → beat map → stills → seek(t) HTML engine → Playwright render → ffmpeg → music/SFX → QA flow, plus asset sourcing (Mixkit, Pexels, Unsplash, svgl, 21st.dev) and every gotcha hit so far.

The studio's Motion Designer. Owns stage 4 (motion graphics) for the studio-director, taking a Motion Brief and delivering a finished motion package (look, storyboard, animated titles, lower thirds, kinetic text, transitions, renders with alpha) plus a handoff report back to the director. Picks and runs the right motion skills (motion-design, remotion-motion-graphics, remotion-graphics, motion-design-html, arabic-motion-typography, web-sims, sound-design, review-loop). Use when the director reaches the motion stage, or when the user asks for motion graphics, an animated intro/outro, a logo reveal, kinetic typography, lower thirds, animated captions or explainer animation, or says "موشن جرافيك", "انيميشن للنص", "انترو متحرك", "عايز موشن للفيديو".

Art-direct animation for websites that mix normal content with "wow" motion — decide what to animate and what to keep still, pick the right tool (CSS, Motion for React, GSAP + ScrollTrigger, Lenis, Three.js/R3F, Lottie, View Transitions), set a motion system (durations, easing, stagger), and keep it fast, accessible and mobile-safe. Use whenever the user wants an animated, interactive, award-style or "keren" website, landing page, portfolio, hero, scroll effect, page transition, or asks "tambahin animasi", "biar lebih hidup", "kayak website Awwwards", even before choosing a library.

Motion tokens, spring presets, performance rules, device adaptation, accessibility enforcement, and SSR safety for React / Next.js using motion/react. Foundation layer — all other motion skills depend on this. Use when setting up motion tokens, spring presets, reduced-motion handling, or SSR-safe animation in React or Next.js.

Production-ready animation patterns for React / Next.js — button, modal, toast, stagger, page transitions, exit animations, scroll, and layout — built on motion-foundations tokens and springs. Use when animating a specific UI element in React or Next.js — button, modal, toast, stagger, page transition, or scroll.

Analyzes Move language packages against the official Move Book Code Quality Checklist. Use this skill when reviewing Move code, checking Move 2024 Edition compliance, or analyzing Move packages for best practices. Activates automatically when working with .move files or Move.toml manifests.

Use for Microsoft 365 tenant administration (Entra ID users, Exchange Online, Teams, licenses, Conditional Access, compliance reports). Plans setup with tenant_setup.py, bulk-manages users with user_management.py and generates PowerShell with powershell_generator.py.

Material-UI v7 component library patterns including sx prop styling, theme integration, responsive design, and MUI-specific hooks. Use when working with MUI components, styling with sx prop, theme customization, or MUI utilities.

Create optimized multi-stage Dockerfiles for any language or framework