Results for “da”

Expert knowledge for Azure Migrate development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Azure Migrate appliances, Arc-based discovery, VMware/Hyper-V moves, AppCAT/CAST scans, or Resource Mover, and other Azure Migrate related development tasks. Not for Azure Database Migration service (use azure-database-migration), Azure Site Recovery (use azure-site-recovery), Azure Virtual Machines (use azure-virtual-machines), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines).

High-converting web design techniques that dazzle and persuade. Covers social proof design, pricing page architecture, CTA optimization, scroll-driven persuasion, interactive demos, trust signals, and the visual craft behind sites that sell. Activate on 'sales page design', 'conversion design', 'high-converting', 'landing page that sells', 'pricing page design', 'social proof', 'dazzle', 'wow factor', 'persuasive design', 'conversion rate', 'make it sell'. NOT for copywriting (use marketing copywriting skills), not for A/B testing setup (use frontend-developer), not for paid ad creative (use marketing skills).

Run the standard single-cell RNA-seq analysis pipeline with Scanpy on AnnData — QC filtering, normalization, dimensionality reduction (PCA, UMAP, t-SNE), Leiden/Louvain clustering, marker/differential expression, PAGA trajectories, and plotting. Use when analyzing scRNA-seq data through clustering, cell-type annotation, DE, or pseudotime workflows; for building or reading the .h5ad data structure itself (layers, obs/var, concatenation, backed mode) prefer alterlab-anndata instead, and for RNA velocity from spliced/unspliced counts prefer alterlab-scvelo instead. Part of the AlterLab Academic Skills suite.

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.

Fully autonomous QA testing agent for Modular RAG MCP Server. Reads test cases from QA_TEST_PLAN.md, executes ALL test types automatically without human intervention — CLI commands, Dashboard UI via Streamlit AppTest headless rendering, MCP protocol via subprocess JSON-RPC, provider switches, and data lifecycle checks. Diagnoses failures, applies fixes with up to 3 retry rounds, and records results in QA_TEST_PROGRESS.md. Use when user says 'run QA', 'QA test', 'QA 测试', '执行测试', '跑测试', 'test and fix', or wants to execute QA test plan.

Fully autonomous QA testing agent for Modular RAG MCP Server. Reads test cases from QA_TEST_PLAN.md, executes ALL test types automatically without human intervention — CLI commands, Dashboard UI via Streamlit AppTest headless rendering, MCP protocol via subprocess JSON-RPC, provider switches, and data lifecycle checks. Diagnoses failures, applies fixes with up to 3 retry rounds, and records results in QA_TEST_PROGRESS.md. Use when user says 'run QA', 'QA test', 'QA 测试', '执行测试', '跑测试', 'test and fix', or wants to execute QA test plan.

Creates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. 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 topologies — applicable to social, biological, transportation, citation, and any pairwise-relationship networks. This is classical graph analytics, not deep learning — for training graph neural networks (GCN/message passing, node/edge/graph classification on Cora-style data) use alterlab-torch-geometric instead. Part of the AlterLab Academic Skills suite.

Kotlin language fundamentals. Covers null safety, coroutines, flow, sealed classes, data classes, scope functions, and Kotlin 2.x features (K2 compiler, context parameters). Use for Kotlin/JVM, Kotlin/Native, Kotlin/JS work. USE WHEN: user mentions "Kotlin", "coroutines", "suspend", "Flow", "sealed class", "data class", "scope functions", "K2 compiler", "ksp", "Kotlin 2.x" DO NOT USE FOR: Kotlin Multiplatform setup - use `mobile/kotlin-multiplatform` DO NOT USE FOR: Compose UI - use `frontend-frameworks/compose-multiplatform` DO NOT USE FOR: Spring Boot Kotlin - use `spring-boot` framework skill

Design and implement programmatic SEO strategies to create search-optimized pages at scale using templates and data, avoiding thin content penalties.

Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants for clean API contracts in Python applications using Pydantic v2.

Fine-tune Cosmos Reason video QA models using supervised fine-tuning with FSDP parallelism, including dataset preparation, spec construction, and AutoML support.

Batch-convert UI design screenshots into Vue 3 Composition API components using Vant, Element Plus, or Ant Design Vue.

Validate an AEM Edge Delivery Services sitemap.xml against actual site content, checking URL reachability, lastmod dates, and identifying missing or orphaned pages.

Automate OpenAI API operations: generate text and multimodal responses with structured output, create embeddings, generate images, and list models via the Composio MCP integration.

Extracts full detail data from a single Goofish (闲鱼) second-hand item page, including title, price, seller info, description, images, tags, and want-count.

Extract Amazon product reviews by ASIN using the BrowserAct API, returning structured data including ratings, text, reviewer info, and verified purchase status.

Scrapes Amazon product data from ASINs using browseract.com automation API and performs competitive analysis, comparing specifications, pricing, review quality, and visual strategies.

Extract structured product details from Amazon using an ASIN, including title, price, ratings, brand, and description via the BrowserAct API.

Extract GitHub repository details and contributor contact information using keywords, star counts, and update dates via the BrowserAct API.

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

Analyze recent screen activity via a local screenpipe daemon, detect repeated research workflows, and draft new skills or composition recipes for uncovered patterns.

Chat with your agent about projects, recommendations, and canonical papers in Paperzilla. Fetch feeds, read papers, leave feedback, and export data using the pz CLI.

Analyze biological sequences, alignments, phylogenetic trees, and diversity metrics (alpha/beta, UniFrac) with ordination (PCoA) and PERMANOVA for microbiome and community ecology data.

Automate OSINT collection using SpiderFoot REST API and CLI for target profiling, module-based reconnaissance, and structured result analysis across 200+ data sources.

Investigate security incidents by correlating Windows event logs, firewall, proxy, and authentication data using Splunk SPL queries and Enterprise Security.

Collects and synthesizes open-source intelligence (OSINT) about threat actors, malicious infrastructure, and attack campaigns using passive reconnaissance tools and public data sources.

Identify AWS IAM privilege escalation paths by analyzing policies for dangerous permission combinations and least-privilege violations using boto3 and Cloudsplaining-style analysis.

Detect LSASS credential dumping, SAM database extraction, and NTDS.dit theft using Sysmon Event ID 10, Windows Security logs, and SIEM correlation rules.

Identifies and exploits SQL injection vulnerabilities in web applications during authorized penetration tests using manual techniques and automated tools like sqlmap.

Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality.

Train reinforcement learning models using torchforge, Meta's PyTorch-native RL library for scalable, algorithm-focused experimentation with GRPO, DAPO, and custom loss functions.

Convert daily market observations and news reactions into structured edge hints, with optional LLM augmentation, outputting a canonical hints.yaml for downstream concept synthesis.

Analyze Framer's marketing site design system, including color palette, typography hierarchy, spacing, and component patterns, to produce a structured design specification.

Annotates single-cell RNA-seq data by scoring marker genes, transferring labels with CellTypist, or reasoning over cluster markers with an LLM.

Index of Odoo 19 development guides covering actions, controllers, data files, decorators, fields, manifests, migrations, mixins, models, OWL components, performance, reports, security, testing, translation, transactions, and views.

Extracts a specified URL parameter (such as loc) from a MySQL text column, derives the domain from each parameter value, and counts occurrences per domain, sorted descending.