Results for “build”

Query NFT and token data, trade NFTs on Seaport, swap ERC20 tokens via DEX aggregator, configure wallet signing providers, and build/register/gate AI agent tools on Base.

Loads and processes whole-slide pathology images, builds spatial graphs, trains deep learning models, and analyzes multiplexed immunofluorescence data across 160+ slide formats.

Bootstraps a two-part _docs directory (_build/ for technical docs, _public/ for research and proposals) with a CONSTITUTION.md governing the split, and can audit or migrate an existing structure.

Builds, refines, tests, or validates a CLI-Anything harness for a GUI application or source repository, producing a stateful Click CLI with JSON output and REPL mode.

Builds a scheduled, AI-powered data collection agent that scrapes public sources, enriches results with Gemini Flash, and stores them in Notion, Sheets, or Supabase.

Run an AI Lab division meeting with research and build agents (no AI Startup agents). Use when the user requests to "start a lab meeting", "convene the lab", or "run a sprint retrospective for the lab".

Nx smart monorepo build system reference. Covers affected commands, computation caching, project graph visualization, nx.json and project.json config, code generators for React/ Angular/Node/Next.js, module boundary enforcement, Nx Cloud remote caching, and migration from Turborepo.

Provides comprehensive NestJS framework patterns with Drizzle ORM integration. Use when building NestJS applications, setting up APIs, implementing authentication, working with databases, or integrating Drizzle ORM. Covers controllers, providers, modules, middleware, guards, interceptors, testing, microservices, GraphQL, and database patterns.

Use when authoring a new manuscript, thesis chapter, or abstract from scratch in Turkish and English in parallel — building the claim skeleton first, then drafting Turkish and re-authoring English — not for auditing parity between existing versions.

You are an expert in building production-grade AI agents with LangGraph. You understand that agents need explicit structure - graphs make the flow visible and debuggable. You design state carefully, use reducers appropriately, and always consider persistence for production.

Expert UI designer specializing in component creation, layout systems, and visual design implementation. Masters modern design patterns, responsive layouts, and design-to-code workflows. Use PROACTIVELY when building UI components, designing layouts, creating mockups, or implementing visual designs.

Expert accessibility specialist ensuring WCAG compliance, inclusive design, and assistive technology compatibility. Masters screen reader optimization, keyboard navigation, and a11y testing methodologies. Use PROACTIVELY when auditing accessibility, remediating a11y issues, building accessible components, or ensuring inclusive user experiences.

This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or requests 3-5 year financial planning for a startup.

Configure Maven, Gradle, and static analysis for Java projects. Use for Java-only build and quality tooling such as Spotless, Checkstyle, SpotBugs, SonarLint, JDK versions, and Java service Dockerfiles; defer Kotlin, Android, Flutter, and GitHub Actions-specific configuration.

Build or upgrade web forms to production quality: accessible structure, schema-driven validation, client↔server parity. Use when "improve this form", "form validation", "accessible form", "multi-step form", "form error handling", or "the form UX is bad".

Build landing pages, portfolios, and marketing sites that don't look AI-generated. Use when asked for "landing page", "portfolio", "marketing site", "anti-slop", "Awwwards-style", "premium frontend", or when design needs a strong point of view.

Expert data engineer specializing in building reliable data pipelines, lakehouse architectures, and scalable data infrastructure. Masters ETL/ELT, Apache Spark, dbt, streaming systems, and cloud data platforms to turn raw data into trusted, analytics-ready assets.

Atomic-design guidance for UI Atoms — the smallest single-purpose building blocks (buttons, inputs, icons, labels). Use when authoring or reviewing components under ui/atoms, components/atoms, or when deciding whether a component belongs at the atom level.

Use when designing AI product trust, privacy, or honesty UX — cloud disclosure, voice/mic consent, transcript retention, memory ownership, AI labeling, caveats, or audit footprints. Trigger on disclose cloud, recording consent, watermark, incognito, or data-ownership settings.

Building interactive experiences that engage, challenge, and delight playersUse when "game, gamedev, game development, phaser, unity, unreal, godot, gameplay, game loop, sprites, collision, physics, player, level, tilemap, games, gamedev, interactive, gameplay, physics, engines, performance, player-experience" mentioned.

Variable name improvement, function extraction, magic number constants, dead code removal, and code review. For refactoring and PR review — does not change behavior. Don't use for bug/security (Judge), new tests (Radar), architecture (Atlas), or feature implementation (Builder).

ZeroMQ notifications from Bitcoin Core: rawblock, rawtx, hashblock, hashtx, sequence. Subscribe over TCP/IPC, integration patterns for Electrs, BTCPay, Lightning nodes. USE WHEN: building real-time integrations with bitcoind, monitoring mempool sequence, integrating LN nodes.

Cashu: single-mint Chaumian e-cash for Bitcoin Lightning. NUTs (Notation, Usage, and Terminology specs) define mint protocol, payment flow, blind signatures. USE WHEN: integrating Cashu mints/wallets, building NUT-compliant apps, comparing with Fedimint.

Use when compiling a LaTeX paper, debugging LaTeX errors, building a paper PDF, or when a .tex file fails to produce output. Handles engine detection (xelatex vs pdflatex), bibliography systems (biber vs bibtex), and multi-pass compilation.

Turn a new rep's start date into a ramp that ends in quota, not confusion. Builds a 30/60/90 onboarding plan with milestones at each gate, a certification bar they have to clear before they carry full load, and the manager touchpoints that catch a slow ramp early. Built for B2B sales managers and enablement, customizable to your role and motion. Trigger on "build an onboarding plan", "30/60/90 for a new AE", "how do I ramp this rep", "certification checklist", "onboarding milestones", or any new-hire ramp.

Build multichannel agents for Microsoft 365, Teams, and Copilot Studio using the Microsoft Agents SDK with aiohttp hosting, AgentApplication routing, streaming responses, and MSAL-based authentication.

Switch the active Jetson target-platform pointer to an existing profile YAML. Use before customize/build/flash to change target; not for authoring profiles — use jetson-init-target instead.

Rebuild kernel-side artifacts (DTBs, OOT modules, kernel Image) from source changes under bsp_sources/ and produce a manifest for staging into a BSP image.

Review Cisco IOS and IOS-XE configurations, choose read-only show commands, check ACL wildcard masks and interface direction, and build safe change-window verification checklists.

Design agents that watch data sources, build candidate prediction-market baskets, draft parameter changes, and hand results to a human for review.

Build native UI with the @expo/ui package: real SwiftUI on iOS and Jetpack Compose on Android rendered from React in an Expo or React Native app.

Build and modify Minecraft server plugins for Paper, Spigot, or Bukkit, covering plugin.yml setup, commands, listeners, schedulers, player state, team/arena systems, persistent progression, economy, configuration, and Adventure text.

Build, refactor, or review macOS menubar apps that use Tuist and SwiftUI, with a focus on Tuist-first workflows, strict architecture boundaries, and reliable local launch scripts.

Build, fit, validate, and compare Bayesian models using PyMC's modern API, including hierarchical models, MCMC sampling, variational inference, posterior predictive checks, and model comparison.

Build clinical deep-learning pipelines with PyHealth: load EHR, signal, and imaging datasets, define prediction tasks, instantiate models, train with the PyHealth Trainer, and compute clinical metrics.

Build and train graph neural networks with PyTorch Geometric, covering node/link/graph classification, message passing layers, heterogeneous graphs, and custom datasets.