estuary-materializations

Plugin estuary-materializations from marketplace estuary in estuary/agent-skills. Commands read from the repo's manifest — 1 month ago.

Skills (38)

• capture-alpaca-create

  Create an Alpaca capture using flowctl to stream stock trade data into Estuary collections. Use when setting up an Alpaca Market Data source for historical and real-time stock trades. Use when user says "capture Alpaca", "stream stock trades", "Alpaca market data", or "connect Alpaca to Estuary".

• capture-generic-create

  Create a capture for ANY Estuary connector using dynamic schema discovery. Use when the user wants to capture from a source that doesn't have a dedicated skill (e.g., Kafka, Salesforce, HubSpot, Stripe, S3, GCS, Kinesis, or any of the 148+ connectors). Use when user says "capture from <source>", "st

• capture-http-ingest-create

  Create an HTTP Ingest (webhook) capture to receive data via HTTP POST requests. Use when setting up webhooks from GitHub, Shopify, Stripe, or any JSON source. Use when user says "set up webhook capture", "HTTP ingest to Estuary", "receive POST requests to Estuary", or "webhook capture".

• capture-hubspot-create

  Create a HubSpot Real-Time capture using flowctl to stream CRM data into Estuary collections. Use when setting up a HubSpot source for contacts, companies, deals, tickets, or other HubSpot resources. Use when user says "capture HubSpot", "stream from HubSpot", "HubSpot CDC", or "connect HubSpot to E

• capture-mongodb-create

  Create a MongoDB CDC capture using flowctl. Use when setting up real-time streaming from MongoDB Atlas, DocumentDB, or self-hosted MongoDB. Use when user says "capture MongoDB", "stream from Mongo", "MongoDB CDC", or "connect MongoDB to Estuary".

• capture-mysql-create

  Create a MySQL CDC capture using flowctl with binlog replication. Use when setting up streaming from MySQL, Amazon RDS MySQL, or Aurora MySQL. Use when user says "capture MySQL", "stream from MySQL", "MySQL CDC", "binlog replication", or "connect MySQL to Estuary".

• capture-postgres-create

  Create a new PostgreSQL CDC capture from scratch using flowctl. Covers all Postgres variants (vanilla, Aurora, RDS, Cloud SQL, Supabase, Neon). Use when user says "capture Postgres", "stream from Postgres", "Postgres CDC", "set up replication slot", or "connect Postgres to Estuary".

• capture-sqlserver-create

  Create a SQL Server CDC capture using flowctl. Use when setting up real-time streaming from SQL Server, Azure SQL, Amazon RDS SQL Server, or Google Cloud SQL. Use when user says "capture SQL Server", "stream from MSSQL", "SQL Server CDC", or "connect SQL Server to Estuary".

• derivation-aggregate-metrics

  Create an Estuary derivation that continuously aggregates metrics (daily totals, running counts, min/max, lifetime revenue) using reduction annotations. Use for real-time dashboards, continuous materialised views, and replacing batch ETL aggregations with streaming. Derivations add complexity and co

• derivation-basics

  Foundation for writing Estuary derivations — what they are, language choice (SQL/TypeScript/Python), project layout, flowctl workflow, stateless vs stateful shuffling, and universal gotchas. Read this before any other derivation-* skill. Use when user says "write a derivation", "how do derivations w

• derivation-filter-transform

  Create an Estuary derivation for stateless filtering, field selection, and per-document field transformation. Use for WHERE clauses, projecting fields, computing new fields from existing ones, or data cleansing. Derivations add complexity and cost — confirm the user wants a derivation before reachin

• derivation-flatten-array

  Create an Estuary derivation that flattens a nested array into one output document per array element. Use for normalising nested JSON, exploding line items, unpacking tags, or producing one-row-per-item tables from arrays. Derivations add complexity and cost — confirm the user wants a derivation bef

• derivation-join-collections

  Create an Estuary derivation that joins two or more collections on a shared key, merging their fields into a single enriched collection. Use for data enrichment, denormalisation, building wide tables for BI, and real-time CDC joins. Derivations add complexity and cost — confirm the user wants a deri

• derivation-python

  Write Estuary derivations in Python — async-generator transforms, Pydantic-typed source/output, optional persistent state, and dependency installation via uv. Use for ML/embeddings, async API calls, or any transform where SQL and TypeScript are awkward. Derivations add complexity and cost (and Pytho

• derivation-stateful-logic

  Create an Estuary derivation with custom SQLite state (internal tables) to make per-document decisions based on accumulated history — account balances, inventory levels, approval workflows, deduplication. Derivations add complexity and cost — confirm the user wants a derivation before reaching for t

• derivation-windowing

  Create an Estuary derivation that maintains a sliding time window of events (e.g. "transfers in the last 24h", "failed logins in the last 5 minutes") using internal SQLite state and readDelay for time-based expiration. Derivations add complexity and cost — confirm the user wants a derivation before

• estuary-catalog-history

  View publication history for catalog resources — who changed what and when. Use when investigating timeline of changes, finding who modified a connector, or correlating changes across capture/collection/materialization chains. Use when user says "what changed", "who changed", "publication history",

• estuary-catalog-status

  Run flowctl catalog status to check the control-plane state of an Estuary resource, or list catalog specs to see which connectors exist and which are active. Use when checking whether a task is running, disabled, or failing, interpreting status output, or enumerating connectors. Use when user says "

• estuary-connector-restart

  Pause and restart Estuary connectors by disabling and re-enabling shards via flowctl. Use when temporarily stopping a connector, performing source/destination maintenance, or forcing a fresh restart to clear transient errors or load updated configs immediately. Use when user says "pause connector",

• estuary-flowctl-setup

  Install and authenticate the flowctl CLI for Estuary. Use when setting up flowctl for the first time, troubleshooting authentication, upgrading to the latest version, or configuring programmatic access for CI/CD. Use when user says "install flowctl", "set up flowctl", "flowctl auth", "how to authent

• estuary-logs

  Search and analyze Estuary task logs with jq filtering. Use when investigating task failures, debugging connector errors, analyzing behavior patterns, or streaming live logs. Use when user says "check logs", "show me logs", "task failing", "why is my capture failing", "why is my materialization fail

• estuary-ssh-tunnels

  Diagnose and fix SSH tunnel connection issues for Estuary captures and materializations. Use when seeing tunnel failures, connection timeouts, or permission denied errors. Use when user says "SSH tunnel failed", "connection timeout via tunnel", "permission denied SSH", "tunnel not working", "network

• estuary-task-health

  Run a comprehensive health check on a single Estuary task by combining catalog status, data flow stats, recent errors, and publication history. Use when diagnosing a task that seems broken, slow, or stuck. Use when user says "is my task healthy", "something seems wrong", "check my capture", "check m

• estuary-task-stats

  Check task processing statistics to see how much data and how many docs are moving. Use when checking throughput, diagnosing a stalled task, verifying data movement, or reporting on task activity. Use when user says "is data flowing", "how much data", "check throughput", "how many documents", "task

• materialize-bigquery-create

  Create a BigQuery materialization to stream Estuary collections into BigQuery tables. Use when setting up BigQuery as a destination for captured data. Use when user says "send to BigQuery", "load into BigQuery", "materialize to BigQuery", or "BigQuery destination".

• materialize-clickhouse-create

  Create a ClickHouse materialization to stream Estuary collections into ClickHouse tables. Use when setting up ClickHouse as a destination for captured data. Use when user says "send to ClickHouse", "materialize to ClickHouse", "ClickHouse destination", or "load into ClickHouse".

• materialize-databricks-create

  Create a Databricks materialization to stream Estuary collections into Databricks tables via Unity Catalog. Use when setting up Databricks as a destination for captured data. Use when user says "send to Databricks", "materialize to Databricks", "Databricks destination", or "load into Databricks".

• materialize-generic-create

  Create a materialization for any Estuary destination connector. Use this generic skill when no dedicated skill exists for the target system. Use when user says "materialize to", "send data to", "destination connector", or "set up materialization".

• materialize-hubspot-create

  Create a HubSpot materialization to write Estuary collections back into HubSpot CRM objects (Contacts, Companies, Deals, Tickets, etc). Use when setting up HubSpot as a destination for captured data. Use when user says "send to HubSpot", "materialize to HubSpot", "write back to HubSpot", or "HubSpot

• materialize-postgres-create

  Create a PostgreSQL materialization to stream Estuary collections into PostgreSQL tables. Use when setting up PostgreSQL as a destination for captured data. Use when user says "send to Postgres", "materialize to PostgreSQL", "Postgres destination", or "load into Postgres".

• materialize-redshift-create

  Create a Redshift materialization to stream Estuary collections into Amazon Redshift tables. Use when setting up Redshift as a destination for captured data. Use when user says "send to Redshift", "materialize to Redshift", "Redshift destination", or "load into Redshift".

• materialize-snowflake-create

  Create a Snowflake materialization to stream Estuary collections into Snowflake tables. Use when setting up Snowflake as a destination for captured data. Use when user says "send to Snowflake", "materialize to Snowflake", "Snowflake destination", or "load into Snowflake".

• schema-custom-types-ddl

  Override default column types in materializations using castToString or custom DDL. Use when column type needs different precision (e.g., NUMERIC(22,6)), VARCHAR length is wrong, need JSONB instead of JSON, integers lose precision, or need to force a string representation. Use when user says "change

• schema-define-fields

  Add or define specific fields in a collection's readSchema. Use when fields are missing from materialization field selection, pruned by complexity limit, need type refinement, need to be protected from future inference changes, or need to be required for downstream consumers. Use when user says "mis

• schema-field-redaction

  Add redaction annotations to sensitive fields in schemas to block or hash PII. Use when configuring GDPR/HIPAA compliance, protecting credentials, or blocking internal fields from materializations. Use when user says "protect PII", "hide sensitive data", "hash field", "redact field", "GDPR complianc

• schema-field-selection

  Control which fields are included or excluded in materializations using depth modes and field overrides. Use when reducing table width, including nested fields, excluding PII, or optimizing performance. Use when user says "exclude fields", "include nested field", "too many columns", "select specific

• schema-null-defaults

  Handle NULL values and set default values for missing fields in collections and materializations. Use when fields need defaults, nullable primary key errors occur, or source data has gaps. Use when user says "NULL values", "default value", "missing field", "nullable primary key error", or "fill in m

• schema-projections

  Add projections to collections to rename fields or map nested JSON paths to flat column names. Use when renaming fields for destination conventions, flattening nested paths to columns, or creating field aliases. Use when user says "rename field", "flatten nested JSON", "map JSON path to column", "fi