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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 before reaching for this (some destinations can `UNNEST` server-side without one). Use when user says "flatten-array derivation", "derivation to explode an array", "transformation to unnest", "derive one row per item", or "flatten nested data with a derivation".

日本語の概要は準備中です。原文の説明を表示しています。

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 derivation before reaching for this (a destination-side SQL join or BI tool view is often simpler). Use when user says "join-collections derivation", "derivation to join two collections", "transformation to enrich with customer data", "derive a wide table", "lookup-join derivation", or "build a join derivation".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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-tunnel failed", "no pubkey loaded", "bastion host not connecting", or "RSA key format".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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 Estuary".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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 destination".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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 Python derivations require a private/BYOC data plane) — confirm the user wants a Python derivation before reaching for this. Use when user says "python derivation", "write a derivation in python", "embed with a python derivation", "ML derivation", "call an API from a derivation", or anything mentioning model2vec / huggingface / pydantic in a derivation context.

日本語の概要は準備中です。原文の説明を表示しています。

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 this. Use when user says "stateful derivation", "derivation to track balance", "transformation to approve based on state", "derive an approval workflow", "deduplication derivation", or "build a stateful derivation".

日本語の概要は準備中です。原文の説明を表示しています。

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 reaching for this. Use when user says "windowing derivation", "derivation for last-24h events", "rolling-window derivation", "sliding-window transformation", "fraud-detection derivation", "rate-limit derivation", or "time-window derivation".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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", "catalog history", "when was it published", "timeline of changes", or "what happened to my connector".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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 "check task status", "is my capture running", "catalog status", "flowctl catalog status", "what's wrong with my capture", "task failing", "check catalog status", "collection status", "derivation status", "why is my task disabled", "list my connectors", "show me my connectors", "list captures", "list materializations", "what connectors do I have", or "show me all my active connectors".

日本語の概要は準備中です。原文の説明を表示しています。

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 column type", "wrong precision", "VARCHAR too short", "integer truncated", "cast to string", or "custom DDL".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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".

日本語の概要は準備中です。原文の説明を表示しています。

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 "missing fields", "pruned fields", "field not showing up", "complexity limit", "define field in read schema", "restrict field type", or "protect field from inference".

日本語の概要は準備中です。原文の説明を表示しています。

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", "stop connector", "restart connector", "disable connector", "enable connector", "re-enable task", "disable shards", "stop my capture", "stop my materialization", "disable my materialization", "force restart connector", "connector maintenance", "temporarily stop processing", "shards disable true", "enable shards", "resume connector", or "unpause connector".

日本語の概要は準備中です。原文の説明を表示しています。