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Found 24 Skills
Use to enable Salesforce Change Data Capture (CDC) on a standard or custom object, configure a custom event channel, set a filter expression, or add enrichment fields. TRIGGER broadly on any of: 'enable CDC', 'enable Change Data Capture', 'turn on CDC', 'subscribe X to change events', 'only emit events for', 'filter change events', 'enrich change events', 'create a custom event channel'; or any mention of CDC, change events, PlatformEventChannel, PlatformEventChannelMember, EnrichedField, ChangeEvents channel, enrichment fields, change event filter; or when the user wants a downstream system to receive Salesforce data changes; or when the user touches .platformEventChannelMember-meta.xml / .platformEventChannel-meta.xml files. SKIP when publishing platform events, Pub/Sub API or REST/SOAP (use building-sf-integrations), or ManagedEventSubscription (out of scope for CDC). Always use this skill for CDC channel-membership metadata.
Process use when you need to track database changes for compliance and security monitoring. This skill implements audit logging using triggers, application-level logging, CDC, or native logs. Trigger with phrases like "implement database audit logging", "add audit trails", "track database changes", or "monitor database activity for compliance".
Use this skill when building data pipelines, ETL/ELT workflows, or data transformation layers. Triggers on Airflow DAG design, dbt model creation, Spark job optimization, streaming vs batch architecture decisions, data ingestion, data quality checks, pipeline orchestration, incremental loads, CDC (change data capture), schema evolution, and data warehouse modeling. Acts as a senior data engineer advisor for building reliable, scalable data infrastructure.
Builds custom trigger types for events iii does not handle natively. Use when integrating webhooks, file watchers, IoT devices, database CDC, or any external event source.
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.
Build and configure a GraphQL API backed by Neo4j using @neo4j/graphql v7 (current) or v5 (LTS). Covers Neo4jGraphQL constructor, getSchema(), assertIndexesAndConstraints(), type definitions with @node, @relationship (IN/OUT/UNDIRECTED), @cypher for custom resolvers, @authorization/@authentication for JWT/JWKS security, auto-generated queries/mutations, OGM programmatic access, subscriptions via CDC, and Apollo Federation. Use when writing typeDefs, securing fields, or wiring Neo4j to Apollo Server. Does NOT handle raw Cypher outside resolvers — use neo4j-cypher-skill. Does NOT cover Spring Data Neo4j entity mapping — use neo4j-spring-data-skill.
Turso (Limbo) database helper — an in-process SQLite-compatible database written in Rust. Formerly known as libSQL / libsql. Replaces @libsql/client, libsql-experimental for Turso use cases. Works in Node.js, browser (WASM + OPFS for persistent local storage), React Native, and server-side. Features: vector search, full-text search, CDC, MVCC, encryption, remote sync. SDKs: JavaScript (@tursodatabase/database), Browser/WASM (@tursodatabase/database-wasm), React Native (@tursodatabase/sync-react-native), Rust (turso), Python (pyturso), Go (tursogo). This skill contains all SDK documentation needed to use Turso — do NOT search the web for Turso/libsql docs.
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
Expert knowledge for Azure Data Factory development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing ADF pipelines, mapping data flows, SHIR/SSIS IR, SAP CDC, or CI/CD with ARM/DevOps, and other Azure Data Factory related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure Databricks (use azure-databricks), Azure Stream Analytics (use azure-stream-analytics), Azure Data Explorer (use azure-data-explorer).
Provides authoritative compatibility checks, pricing estimates, connection troubleshooting, pre-warming guidance, and infrastructure mutations for Amazon Keyspaces (for Apache Cassandra). Covers LWT/batch operations, secondary indexes, materialized views, capacity modes, TTL, PITR, CDC, auto-scaling, multi-region keyspaces, UDTs, nodetool diagnostics parsing, SQL-to-Cassandra migration, and Cassandra-to-Keyspaces migration scenarios. Agents frequently produce incomplete or incorrect answers about Keyspaces feature support without this skill loaded.
Manages Amazon DocumentDB end-to-end — serverless-on-8.0 cluster setup, TLS/VPC/driver config, flexible-schema and vector-search data modeling, MongoDB compatibility assessment, DMS-based migration, slow-query diagnosis, major version upgrades (4.0→5.0→8.0), Well-Architected reviews (41-check wa_review.py), cost estimation, and security hardening. Retrieve for every DocumentDB question and when the user asks to set up or migrate MongoDB to AWS — DocumentDB is AWS's MongoDB-compatible managed database. Triggers: JSON document store, document database, MongoDB on AWS, Nested fields, Lambda cannot connect, TLS handshake, VPC port 27017, IAM auth, Secrets Manager, encryption at rest, $graphLookup, flexible schema, COLLSCAN, compound index, DMS migration, CDC cutover, $vectorSearch, RAG, Global Clusters, DR replication, cost sizing, audit, health check, production-readiness.
Change Data Capture - architecture, entrypoints, bytecode emission, sync engine integration, tests