Use when writing or reviewing Python code in this repo that calls Deepgram Text-to-Speech v1 (`/v1/speak`) for audio synthesis. Covers one-shot REST (`client.speak.v1.audio.generate`) and streaming WebSocket (`client.speak.v1.connect`). Also covers the in-repo `deepgram.helpers.TextBuilder` for incremental text assembly before synthesis. Use `deepgram-python-voice-agent` when you need full-duplex STT + LLM + TTS with barge-in. Triggers include "TTS", "speak", "synthesize voice", "aura", "text to speech", "speak.v1", "TextBuilder".

Multi-perspective investigation. Recommends analytical lenses or assembles a team to analyze from selected viewpoints when the right framework is absent, producing a framed inquiry. Type: (FrameworkAbsent, AI, SELECT, Inquiry) → FramedInquiry. Alias: Prothesis(πρόθεσις).

Infer context insufficiency before execution. Surfaces uncertainties through information-gain prioritized inquiry when AI infers areas of context insufficiency, producing informed execution. Type: (ContextInsufficient, AI, INQUIRE, Prospect) → InformedExecution. Alias: Aitesis(αἴτησις).

This skill should be used when the user asks to "verify protocols", "check consistency before commit", "validate definitions", "run pre-commit checks", "verify soundness", or wants to ensure epistemic protocol quality. Invoke explicitly with /verify for pre-commit validation.

Manage local Airflow environment with Astro CLI (Docker and standalone modes). Use when the user wants to start, stop, or restart Airflow, view logs, query the Airflow API, troubleshoot, or fix environment issues. For project setup, see setting-up-astro-project.

Send SMS messages with Azure Communication Services SMS Java SDK. Use when implementing SMS notifications, alerts, OTP delivery, bulk messaging, or delivery reports.

Build real-time chat applications with thread management, messaging, participants, and read receipts.

⚠️ DEPRECATED: This SDK has been renamed to Call Automation. For new projects, use azure-communication-callautomation instead. This skill is for maintaining legacy code only.

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.

Check branch changes for common PR readiness issues (missing tests, missing JSDoc, guideline violations). Use when the user asks to verify changes before opening a PR, check code quality, or audit a branch for missing items.

Generate Gherkin-format manual testing steps from code changes for pull request descriptions. Use when the user asks for manual testing steps, Gherkin test scenarios, or QA steps for a PR.

Creates or removes a git worktree using the project scripts and shared config. Use when the user asks to create a worktree, add a worktree, remove a worktree, delete a worktree, or work on a parallel branch in a separate directory.

Identify code owners for changed files and map them to Slack group handles. Use when the user asks who owns changed files, which teams to tag for review, or to find code owners for a PR.

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

Build custom Python data sources for Apache Spark using the PySpark DataSource API — batch and streaming readers/writers for external systems. Use this skill whenever someone wants to connect Spark to an external system (database, API, message queue, custom protocol), build a Spark connector or plugin in Python, implement a DataSourceReader or DataSourceWriter, pull data from or push data to a system via Spark, or work with the PySpark DataSource API in any way. Even if they just say "read from X in Spark" or "write DataFrame to Y" and there's no native connector, this skill applies.

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.

Build production-quality search experiences (autocomplete, search results pages, faceted search) using InstantSearch. Use when user asks to add search, autocomplete, search-as-you-type, faceted filtering, or a search results page to a React, Vue, or vanilla JS application, or mentions Algolia, InstantSearch, or react-instantsearch. Do NOT use for backend index operations (records, synonyms, settings, API keys), use algolia-cli instead. Do NOT use for analytics, recommendations, or MCP server queries, use algolia-mcp instead. Do NOT use for AI/agent/conversational search, use algobot-cli instead.