confluentinc

Set up end-to-end Change Data Capture (CDC) pipelines on Confluent Cloud using Debezium source connectors, Flink for transformation, and Tableflow for data lake integration. Supports JSON_SR, Avro, and Protobuf formats. Handles schemaless topics (plain JSON without SR) and multi-event topics. This skill handles the complete workflow from database to Iceberg/Delta tables. Use this skill when users want to capture database changes and materialize them into Iceberg or Delta Lake tables via Confluent Cloud Tableflow. Trigger phrases include "CDC to Tableflow", "database to Iceberg", "database to Delta Lake", "stream database changes to data lake", "set up Tableflow pipeline", "schemaless topic to Tableflow", or "multi-event topic to Iceberg". Do NOT trigger for general CDC, Debezium, or database replication requests that do not involve Tableflow or Iceberg/Delta Lake as the destination.

Create Confluent-specific skills for external users. Use this skill when users want to create, build, or author a new skill related to Confluent Cloud, Confluent Platform, Apache Kafka, WarpStream, Flink, Connectors, Schema Registry, Tableflow, CDC pipelines, or any Confluent product. Skills can be use-case focused (like data enrichment, CDC to Tableflow, stream processing workflows) or component-specific (like a Flink skill, Schema Registry skill, or Connector skill). Do NOT use this skill when users want to directly use Confluent products (e.g., build a pipeline, write a producer, deploy Flink SQL) — use the appropriate product-specific skill instead. This skill is specifically for creating new skills, not for using existing ones.

Review a Confluent agent skill in this repo against the Agent Skills spec (agentskills.io), Confluent conventions in CLAUDE.md, the PR template gates, and the evals-as-contract rule. Use this skill whenever the user asks to review, audit, validate, or lint a skill; opens or inspects a PR that adds or modifies anything under `skills/`; asks about spec conformance, lazy-loading, frontmatter shape, trigger overlap, or eval coverage; or wants a pre-merge sanity check on skill changes. Do NOT trigger for general code review of application code; security review; auditing schemas, producer/consumer configs, PII tagging, or Terraform generation for Schema Registry (handled by `kafka-schema-registry`); runtime/log analysis of skill behavior (use `tools/skill_review_dashboard.py`); or any changes that don't touch the `skills/` tree.

Use when the user wants to build a Python Kafka producer or consumer, add Schema Registry to existing Python code, migrate from raw JSON to schema-backed serialization, or scaffold a confluent-kafka-python project for Confluent Cloud, local Docker, or WarpStream. Also use when user wants to optimize Python Kafka client configuration for WarpStream.

Build and deploy Apache Flink user-defined functions (UDFs) in Java for stream processing over Kafka. Use this skill when users want to create scalar UDFs, user-defined table functions (UDTFs), or process table functions (PTFs) in Java, deploy them to Confluent Cloud or local Docker environments, and invoke them from Flink SQL or the Table API. Trigger on: Flink UDF, custom Flink function, process table function, PTF, UDTF, Flink user defined, extend Flink SQL, stateful stream processing with Flink. Do NOT trigger for: Kafka Streams UDFs (use kafka-streams-programming skill), general Flink job development without custom functions, CDC streaming data piplines that include Flink (prefer the confluent-cloud-cdc-tableflow skill), Flink connector setup, or Kafka producer/consumer code.

Scan a project to identify Kafka applications, extract schemas from data models, tag PII fields, generate Terraform for Confluent Schema Registry registration, and produce a migration report with rollout ordering. Use this skill when a user asks to analyze a folder or repo for Kafka usage, extract schemas, audit producer/consumer configurations, or generate Terraform for Schema Registry.

Architect, build, and debug Kafka Streams apps (JVM-embedded stream processing). Use when user mentions KStream, KTable, topology, TopologyTestDriver, StreamsBuilder, interactive queries, GlobalKTable, joins/windows/aggregations, or debugging issues (rebalancing, state stores, lag, deserialization errors). Also use when user wants to optimize Kafka Streams for WarpStream or tune Kafka Streams client configuration for WarpStream. Do NOT trigger for Flink, connectors, CDC, or plain producer/consumer.

Generate a Schema Registry compatibility report for Avro schemas in a project. Use when the user asks to check Avro compatibility, validate schema evolution, or report breaking changes. Do NOT trigger for Protobuf, JSON Schema, or Kafka client code generation.

Use when the user asks about Mocha test runner APIs and patterns for unit tests. Triggers on questions like "Mocha hooks", "before/after setup", "describe/it structure", "async tests in Mocha", "test timeouts", ".only/.skip", "how to run a specific test", or test organization.

Use when the user asks about Playwright APIs, selectors, assertions, or patterns for E2E or functional tests. Triggers on questions like "how to click a button in Playwright", "Playwright locator", "page.waitFor", "expect toBeVisible", "Playwright test fixtures", or E2E test patterns.

Use when E2E Playwright tests fail, CI reports test failures, the user mentions "triage", "test failed", "flaky test", or wants to debug Electron/Playwright test results. Also use when investigating trace.zip files, test screenshots, or Playwright HTML report archives from CI.

Reviews pull requests for this VS Code extension. Use when reviewing PRs, doing self-review before sharing with the team, or when user mentions "review PR", "review changes", "self-review", or "check my PR". Focuses on project-specific patterns and critical requirements.

Use when the user asks about Sinon stubbing, spying, mocking, or test double APIs for unit tests. Triggers on questions like "how do I stub this", "Sinon fake timers", "spy vs stub", "sandbox usage", "assert.calledWith", "stub.resolves", "sinon.match", or test double patterns.

Use when the user asks about VS Code API definitions, methods, interfaces, events, types, or wants to understand what VS Code APIs are available. Triggers on questions like "what does vscode.X do", "how to use VS Code API", "VS Code type definition", or checking API compatibility.

Reviews pull requests for the Confluent MCP server. Use when reviewing PRs, doing self-review before sharing with the team, or when the user mentions "review PR", "help with PR", "review changes", "self-review", "review local changes", or "check my PR". Focuses on MCP tool wiring, OpenAPI/type coupling, ESM stubbability, transport security, and project-specific patterns.

Use when the user asks about Model Context Protocol details (protocol spec, transports, authorization, tools/resources/prompts, sampling/elicitation/roots, server/client concepts, extensions, or SDK usage). Triggers on phrases like "MCP spec", "MCP transport", "streamable HTTP", "MCP authorization", "list_tools", "initialize handshake", "MCP SDK", "@modelcontextprotocol/sdk", or "how does MCP X".

Use when the user asks about Vitest mocking, spies, stubs, fake timers, config, or test runner behavior. Triggers on questions like "vi.fn", "vi.spyOn", "vi.mocked", "Mocked<T>", "mockResolvedValue", "restoreMocks", "vitest mock", "createMockInstance", "useFakeTimers", or how to accomplish test double patterns with Vitest.

IntelliJ Platform SDK lookup for plugin development. Use when the user asks about IntelliJ Platform APIs, extension points, threading rules, PSI, VFS, services, UI components, or how to implement plugin features. Triggers on questions like "how do I create a tool window", "what's the API for X", "IntelliJ threading rules", or checking platform API compatibility.

Guide writing unit tests for the Kafka IntelliJ plugin. Use when the user asks to "write tests", "add unit tests", "test this component", or needs help testing services, actions, UI panels, or data models in isolation. Also triggers on "how do I test", "mock service", "test action", or "test UI panel".

Review pull requests for the Kafka IntelliJ plugin. Checks for IntelliJ Platform best practices, threading safety, proper service usage, localization, and project-specific patterns. Use when reviewing PRs, doing self-review before sharing with the team, or when user mentions "review PR", "help with PR", "review changes", "self-review", "review local changes", or "check my PR".

Use when the user asks about GraalVM native image compilation, reflection registration, native build failures, or native executable testing. Triggers on questions like "@RegisterForReflection", "native image build error", "reflection-config.json", "native library loading", "GraalVM substitution", "--initialize-at-run-time", "native executable test", "native build args", "ClassNotFoundException in native", or "make test-native".

Reviews pull requests for the ide-sidecar project. Use when reviewing PRs, doing self-review before sharing with the team, or when user mentions "review PR", "help with PR", "review changes", "self-review", "review local changes", or "check my PR". Provides generic PR Review skill with project-specific patterns and tech stack-related requirements.

Use when the user asks about Quarkus framework APIs, CDI dependency injection, SmallRye Mutiny reactive programming, JAX-RS REST endpoints, Quarkus testing, or application configuration. Triggers on questions like "how does @Inject work", "Uni vs Multi", "Quarkus test profile", "application.yml config", "@ApplicationScoped vs @Singleton", "@Produces bean", "@Observes event", "CDI observer pattern", "Mutiny transform", "Vert.x HTTP client", or "Quarkus guide for X".