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Found 1,641 Skills
Configure and operate the Neo4j Connector for Kafka (sink + source) and the native Neo4j CDC API. Covers Cypher/Pattern/CUD sink strategies, CDC-based and query-based source, exactly-once semantics, DLQ error handling, Confluent Cloud managed connector, schema registry (Avro/JSON), and native db.cdc.query cursor-loop patterns (Neo4j 5.13+ Enterprise/Aura BC/VDC). Use when streaming Kafka events into Neo4j, streaming Neo4j changes to Kafka, or querying Neo4j change events without Kafka. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle bulk CSV/file import — use neo4j-import-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.
System exploitation testing - Active Directory attacks, privilege escalation (Linux/Windows), and exploit development.
Scaffolds Remotion project folder structure, base configuration files, and file organization. Focuses ONLY on directory creation, empty file templates, and Remotion configuration. Use when starting a new video project or when asked to "scaffold Remotion project", "create project structure", "setup Remotion folders".
Build production RAG systems with semantic chunking, incremental indexing, and filtered retrieval. Use when implementing document ingestion pipelines, vector search with Qdrant, or context-aware retrieval. Covers chunking strategies, change detection, payload indexing, and context expansion. NOT when doing simple similarity search without production requirements.
Open Orbit briefing skill — selected by the Orbit pipeline when the user has two or more connectors connected. Pulls the past 24 hours of activity from every authenticated connector (GitHub, Linear, Notion, Slack, 飞书, Calendar, Gmail, Drive, Sentry, Vercel, …) and renders a single adaptive bento-grid dashboard at the top of "我的设计". Each connector module picks its own UI form (list, avatar stack, status ring, heatmap, file grid, alert card, …) based on the data shape it returns, so the layout scales as Orbit's connector ecosystem grows. This skill should not be triggered manually — it is invoked by Orbit's daily-digest scheduler against the user's live connector data.
Generate a Dynatrace Gen 3 **KPI dashboard** (15–20 business KPIs, required map tile, branded section dividers) and a matching 30‑minute BizEvents injector for a named company, then deploy both via `dtctl`. Use this skill ONLY when the user explicitly asks for a Dynatrace KPI dashboard, business-event KPI demo, BizEvents injector, or a "KPI dashboard for <company>" — do NOT use for generic Dynatrace dashboards (SRE, infra, k8s, services, RUM) or for editing existing non-KPI dashboards. Triggers include phrases like "generate a KPI dashboard", "build a BizEvents demo for <company>", "spin up a KPI dashboard + injector", "/generate-kpi-dashboard". Requires `dtctl` authenticated to a Dynatrace Gen 3 tenant.
Agent-agnostic visual feedback tool for AI coding agents to identify and annotate UI elements with structured selectors
Process raster data: clip by bounding box, stack multiple bands, mosaic GeoTIFFs, or convert between raster and vector formats.
Workflow required before any Mule flow and integration work. Call use_skill as your FIRST action — before reading project files — whenever the user asks to create, generate, update, fix, modify, change, edit, tweak, adjust, or rework any Mule flow, sub-flow, or component. Do not read project files and attempt the change yourself — even targeted single-component changes like 'modify the choice router', 'fix the until-successful', or 'update the catch block' require this workflow. Covers all change types, new integrations and targeted changes to error handlers, catch blocks, choice routers, DataWeave transforms, HTTP listeners, foreach loops, retry policies, scatter-gathers, connectors, and variable assignments. Prompts beginning with 'This code defines...' or 'This flow...' are generation requests, not analysis. When you call this skill, it must be the only tool call in that response.
RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools for trajectory inference.
Use this skill when editing or creating CLI output, logging, warnings, error messages, progress indicators, or diagnostic summaries in the APM codebase. Activate whenever code touches console helpers (_rich_success, _rich_warning, _rich_error, _rich_info, _rich_echo), DiagnosticCollector, STATUS_SYMBOLS, CommandLogger, or any user-facing terminal output — even if the user doesn't mention "logging" or "UX" explicitly.
Pricing completo de opciones europeas y americanas. 9 metodos: Black-Scholes, Binomial CRR, Trinomial, Monte Carlo (antithetic) + Longstaff-Schwartz, Bjerksund-Stensland 2002 / BAW (American closed-form), Heston 1993 (vol estocastica, sonrisa via Fourier), Bates 1996 (Heston + Merton jumps, crash risk), greeks (BS), implied vol, P(ITM) y P(Profit). Disenado para backtesting: cada funcion es flat Python vectorizado con numpy (sin abstracciones), usa math.erfc (no scipy). BS 2.4 us/op, BS2 3.6 us, Heston 400 us, Binomial N=500 5.6 ms. CLI con 15 modos mas validate y bench. Time complexity O(1) para todos los closed-form.