Skill do QA Engineer para testes unitarios, integracao e E2E. Use quando precisar escrever testes, validar regressao, revisar cobertura, configurar estrategia de QA, ou evidenciar qualidade antes de release. Trigger em: "teste", "test", "QA", "Playwright", "Vitest", "Jest", "E2E", "coverage", "mock", "fixture", "regressao", "teste de integracao", "testing library".

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

Migrate between Kling AI model versions safely. Use when upgrading from v1.x to v2.x or adopting new features. Trigger with phrases like 'klingai upgrade', 'kling ai migrate', 'klingai version update', 'upgrade kling model'.

Runs Fastly Compute WASM applications locally with Viceroy, specifically for Rust and Component Model projects. Use when starting a local Fastly Compute dev server with Viceroy, configuring fastly.toml for local backend overrides and store definitions, running Rust unit tests with cargo-nextest against the Compute runtime, debugging Compute apps locally, adapting core WASM modules to the Component Model, or troubleshooting local Compute testing issues (connection refused, missing backends, store config). For non-Rust Compute work or understanding the Compute API, prefer the fastlike skill instead — its source code is easier to understand as a Fastly Compute API reference.

Search, create, and manage notes in the Obsidian vault with wikilinks and index notes. Use when user wants to find, create, or organize notes in Obsidian.

Guides writing grammY Telegram bot handlers, middleware, and plugins. Use when creating or modifying bot commands, inline queries, callback queries, message handlers, or middleware.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Create and edit Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, and other Obsidian-specific syntax. Use when working with .md files in Obsidian, or when the user mentions wikilinks, callouts, frontmatter, tags, embeds, or Obsidian notes.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Clean up old cached plugin versions to free disk space. Use when the user says "clean cache", "cleanup plugins", "prune old versions", "free disk space", "plugin cache", "clear old plugins", or asks about plugin cache size.

Designs or reviews CLIs so coding agents can run them reliably: non-interactive flags, layered --help with examples, stdin/pipelines, fast actionable errors, idempotency, dry-run, and predictable structure. Use when building a CLI, adding commands, writing --help, or when the user mentions agents, terminals, or automation-friendly CLIs.

Discover available tools and resources in Databricks workspace. Use when: (1) User asks 'what tools are available', (2) Before writing agent code, (3) Looking for MCP servers, Genie spaces, UC functions, or vector search indexes, (4) User says 'discover', 'find resources', or 'what can I connect to'.

Apache Iceberg tables on Databricks — Managed Iceberg tables, External Iceberg Reads (fka Uniform), Compatibility Mode, Iceberg REST Catalog (IRC), Iceberg v3, Snowflake interop, PyIceberg, OSS Spark, external engine access and credential vending. Use when creating Iceberg tables, enabling External Iceberg Reads (uniform) on Delta tables (including Streaming Tables and Materialized Views via compatibility mode), configuring external engines to read Databricks tables via Unity Catalog IRC, integrating with Snowflake catalog to read Foreign Iceberg tables

Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, working with Kafka ingestion, implementing Real-Time Mode (RTM), configuring triggers (processingTime, availableNow), handling stateful operations with watermarks, optimizing checkpoints, performing stream-stream or stream-static joins, writing to multiple sinks, or tuning streaming cost and performance.

Start AEM Workflows on AEM as a Cloud Service using all available triggering mechanisms. Use when starting workflows manually via the Timeline UI, programmatically via WorkflowSession.startWorkflow(), via the HTTP Workflow API, through Manage Publication, or passing initial metadata and payload to a workflow instance.

Start AEM Workflows on AEM 6.5 LTS using all available triggering mechanisms. Use when starting workflows manually via the Timeline UI, programmatically via WorkflowSession.startWorkflow(), via the HTTP Workflow API, through Manage Publication, through replication triggers, or passing initial metadata and payload to a workflow instance.

Implement custom AEM Workflow Java components on AEM 6.5 LTS. Use when writing WorkflowProcess steps, ParticipantStepChooser implementations, registering services via Felix SCR or DS R6 OSGi annotations, reading step arguments from MetaDataMap, accessing JCR payload via WorkflowSession adapter, reading and writing workflow metadata and variables, and handling errors with WorkflowException for retry behavior.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Use when writing or reviewing Java code in this repo that calls Deepgram Conversational STT v2 / Flux over `/v2/listen`. Covers `client.listen().v2().v2WebSocket()`, `V2ConnectOptions`, `onTurnInfo`, and turn-aware close handling. Use `deepgram-java-speech-to-text` for standard v1 transcription and `deepgram-java-voice-agent` for fully interactive assistants. Triggers include "flux", "conversational stt", "listen v2", "turn detection", "end of turn", and "eot".