Results for “build”

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.

Expert AI/ML engineer specializing in machine learning model development, deployment, and integration into production systems. Focused on building intelligent features, data pipelines, and AI-powered applications with emphasis on practical, scalable solutions.

Configure secure, high-performance connectivity between on-premises infrastructure and cloud platforms using VPN and dedicated connections. Use when building hybrid cloud architectures, connecting data centers to cloud, or implementing secure cross-premises networking.

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

Build structured knowledge graphs from unstructured text by extracting entities, mapping relationships, generating graph triples, and visualizing the result. Use when the user requests knowledge graph creation or provides relevant inputs for this workflow.

Specialized hardware interfaces and system reliability for Zephyr RTOS. Covers LVGL GUI development, Audio I2S/Codecs, Watchdog timers, and Fault Injection. Trigger when building human-machine interfaces (HMI), audio devices, or high-reliability mission-critical systems.

Converting document formats (Markdown/Word/Excel/PDF/HTML). Converts specs from Scribe and reports from Harvest into distributable formats; generates reusable conversion scripts. Use when converting documents, building accessibility-compliant PDFs, or creating Pandoc/LibreOffice pipelines.

Guides Claude in writing idiomatic, efficient, well-structured Rust code using proper data modeling, traits, impl organization, macros, and build-speed best practices. TRIGGER when working on .rs files or Rust projects (Cargo.toml present).

State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

Build a stakeholder map using a power/interest grid, identify communication strategies per quadrant, and generate a communication plan. Use when managing stakeholders, preparing for a launch, aligning cross-functional teams, or planning stakeholder engagement.

Simulator.Company graph structure specialist. Use when the user wants to build, edit, analyze, inspect, or ask questions about business process graphs, flowcharts, algorithms, actors (nodes), links (edges), or layers (visual views) in Simulator.Company. Trigger on any of these intents: — Creating: "create graph", "build flowchart", "new diagram", "add actor", "add block to graph", "create algorithm", "draw flowchart", "digital twin", "create process on graph", "build process diagram", "FlowchartBlock", "startStop", "predefinedProcess". — Editing: "edit graph", "update actor", "rename node", "change color", "move actor", "add step to flowchart", "modify diagram", "restructure process", "add edge", "remove link", "reorder steps", "update layer". — Syncing: "push graph", "pull graph", "sync graph", "push changes", "apply edits to layer". — Querying / analysis: "what actors are on this layer", "show me the graph", "who is connected to", "find actor", "list nodes", "describe the process", "analyze the flowchart",

Import raw data (CSV, XLSX, TXT, or MATLAB tables) into formats used by Sensor Fusion and Tracking Toolbox. Handles both ground truth trajectories and sensor detection data. For truth: builds trackingScenarioRecording, tuning timetable, truthlog, or converted table. For sensor data: builds task-oriented dataFormat structs (preferred) or objectDetection arrays (legacy). Use when importing flight logs, GPS logs, radar detections, IR measurements, lidar/camera bounding boxes, ADS-B data, AIS ship tracks, or any recorded data for use with trackers, filter tuning, or tracker evaluation.

Design MVPs, validated learning experiments, and pivot-or-persevere decisions using Build-Measure-Learn. Use when the user mentions "MVP scope", "validated learning", "pivot or persevere", "vanity metrics", "test assumptions", "innovation accounting", "build-measure-learn", or "minimum viable experiment". Also trigger when deciding what to include in a first version, measuring startup progress, or evaluating whether to change direction on a product bet. Covers innovation accounting and actionable metrics. For 5-day prototype testing, see design-sprint. For customer motivation analysis, see jobs-to-be-done.

Generate driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder.* sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BUILD, EXPORT, or AUGMENT a virtual scenario/scene/map: ego or actor trajectories, trajectory smoothing, OpenCRG road-surface extraction, 3D asset generation, static-object placement, point-cloud georeferencing + elevation, lane-based ego localization, sensor-fusion tracking, scenario-event extraction (cut-ins, hard brakes, near-misses, ADAS disengagements), or export to RoadRunner, drivingScenario, OpenDRIVE, OpenCRG, OpenSCENARIO, or Unreal Engine. Also: log-to-scenario, scenario harvesting, accident/near-miss reconstruction, SOTIF (ISO 21448) and ISO 26262 scenario coverage, USGS-aerial-lidar augmentation, traffic-sign placement, vision-based vehicle classification for actor assets. NOT for raw-data import or multi-sensor sync/crop/offset/timestamp normalization — route those to matlab-import-driving-data.

Turn an at-risk account into a churn-save play. It diagnoses the real reason behind the risk (not the stated one), lays out the commercial and non-commercial levers you can pull, and builds a multi-touch save sequence with owners and dates. Built for B2B customer success teams, customizable to your CRM and product analytics. Trigger on "this account is going to churn", "build a save play", "why are they leaving", "at-risk renewal", "how do I keep this account", or any retention rescue.

Quantify security risks in dollars, build compliance roadmaps (SOC 2, ISO 27001, HIPAA, GDPR), and justify security budgets for growth-stage companies.

Analyzes RFP/RFI responses for coverage gaps, builds competitive feature comparison matrices, and plans proof-of-concept engagements for pre-sales engineering.

Execute implementation plans by dispatching a fresh subagent per task, with task review after each and a whole-branch review at the end.

Build AI applications on Microsoft Foundry using the Azure AI Projects Python SDK, including agent creation, tool integration, thread management, and evaluation.

Build real-time messaging applications using Azure Web PubSub SDKs for JavaScript, including server-side management, client-side pub/sub, and Express event handlers.

Build search applications with full-text, vector, semantic, and hybrid search using the Azure AI Search SDK for .NET.

Generates or updates a governance skill card for an existing agent skill directory by analyzing source signals, building a grounded JSON context, and rendering a deterministic markdown card.

Browse available agent personas and compose ad-hoc teams of up to 5 agents to work in parallel on a task, then synthesize their results.

Runs a comprehensive verification pipeline for Quarkus projects including build, static analysis, tests with coverage, security scans, native compilation, and diff review before PRs or releases.

Provides expert guidance on modern Java 21+ development, including virtual threads, Spring Boot 3.x, GraalVM, and cloud-native patterns for building scalable enterprise applications.

Build augmented reality interfaces for display glasses using Jetpack Compose Glimmer, covering design principles, theming, input mapping, and projected activity setup.

Generates and writes unit tests for any programming language using a multi-agent pipeline that researches, plans, and implements tests with build and verification steps.

Detects and fixes common MSBuild anti-patterns in .csproj, .vbproj, .fsproj, .props, .targets, and .proj files, covering Exec misuse, unquoted conditions, hardcoded paths, and more.

Prevents misguided optimization of MSBuild's ResolveProjectReferences target by explaining that its reported time is wall-clock wait time, not CPU work, and redirects to task self-time analysis.

Build and optimize Power BI semantic models with star schema design, DAX measures, relationships, and row-level security following Microsoft best practices.

Build scroll animations, parallax effects, pinned sections, and scroll-triggered reveals using GSAP ScrollTrigger or Framer Motion in vanilla JS, React, or Next.js.

Build production-ready React Native and Expo apps with guidance on components, styling, animations, navigation, state management, forms, networking, performance, testing, and deployment.

Explains the advantages of building on Ethereum, including ERC-8004 identity, x402 payments, composability, and permissionless deployment, while correcting common misconceptions about gas costs and network status.

Train unsupervised machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.