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Estuary Agent Skills

Estuary Agent Skills let you create and operate Estuary pipelines from an AI coding assistant. Each skill is a small instruction set that teaches your assistant how to run a specific flowctl workflow, such as creating a Postgres capture, materializing into Snowflake, or diagnosing a failing task.

Skills are distributed from the open-source estuary/agent-skills repository and follow the open SKILL.md standard. They work with Claude Code, Cursor, OpenAI Codex, GitHub Copilot, Gemini CLI, and other compatible tools.

Prerequisites​

Before installing the skills, make sure you have:

What's included​

Skills are grouped into plugins by workflow area, including operations, captures, derivations, materializations, and schema.

info

New skills are added to agent-skills over time, so the summaries below may not be exhaustive. For the current list, browse the estuary/agent-skills repository, or run /plugin in Claude Code and open the Discover tab.

Operations​

Manage and troubleshoot running pipelines: check task health, review logs, inspect data volume and throughput, look at publication history, restart connectors, and diagnose SSH tunnel issues. Install this one first — it's useful on every task, regardless of source or destination.

Captures (sources)​

Capture data from databases, APIs, and webhooks into Estuary collections. Dedicated skills cover Postgres, MySQL, MongoDB, and SQL Server CDC, plus HTTP webhook ingestion. A generic skill configures any of the 150+ source connectors via dynamic schema discovery.

Derivations (transformations)​

Transform, aggregate, and reshape collections in streaming SQL, TypeScript, or Python: filtering and field selection, aggregations like running totals and min/max, joins across collections, array flattening, stateful logic such as balances or approval workflows, and time-based windowing.

Materializations (destinations)​

Stream Estuary collections into downstream databases and warehouses. Dedicated skills cover Postgres, Snowflake, BigQuery, Redshift, and Databricks. A generic skill handles any other destination connector.

Schema​

Shape collection and materialization schemas after the fact: rename or remap fields, control which fields materialize, override column types, redact or hash sensitive fields, set defaults for missing values, and add fields pruned by the schema complexity limit.

Installation​

Installation steps depend on which assistant you use. After installing, restart your assistant if it doesn't pick up the new skills automatically.

Claude Code includes a plugin marketplace. Add the Estuary marketplace:

/plugin marketplace add estuary/agent-skills

Then install the plugins you want:

/plugin install estuary-operations@estuary
/plugin install estuary-captures@estuary
/plugin install estuary-derivations@estuary
/plugin install estuary-materializations@estuary
/plugin install estuary-schema@estuary

You can also run /plugin and browse skills from the Discover tab. Installed skills update automatically when the marketplace refreshes.

To verify, ask Claude: "What Estuary skills do you have?" and confirm the relevant skills are listed.

Walkthrough: your first pipeline​

Once a skill group is installed and flowctl is authenticated, you can drive Estuary from natural-language prompts. A typical first run looks like this.

1. Confirm flowctl is ready​

Ask your assistant:

"Check that flowctl is installed and I'm authenticated to Estuary."

This invokes the estuary-flowctl-setup skill, which checks your CLI version, refreshes your auth token, and points you at the flowctl installation docs if anything is missing.

2. Create a capture​

Describe the source:

"Capture my Postgres database into Estuary. The host is db.example.com, database analytics, and I want all tables in the public schema."

The matching capture-*-create skill discovers your schema, drafts a capture spec, guides you through replication slot setup, and publishes the capture with flowctl.

3. Materialize into a destination​

"Materialize the collections I just captured into Snowflake."

The materialize-snowflake-create skill collects your warehouse, account, and role, generates the materialization spec, and publishes it. The same pattern works for BigQuery, Redshift, Databricks, Postgres, or any other destination through materialize-generic-create.

4. Troubleshoot and operate​

When something goes wrong, ask:

"Why is my materialization to Snowflake failing?"

"Is data flowing through my Postgres capture?"

"Show me what changed on this task in the last week."

These prompts route to the operations skills (estuary-task-health, estuary-task-stats, estuary-logs, estuary-catalog-history), which pull data from flowctl and summarize the results.

If a skill itself misbehaves, file an issue on the agent-skills repo or reach out in the Estuary Slack community.

Example prompts​

Use the skills for any task you would normally run by hand:

  • "Capture from MySQL and materialize into Redshift."
  • "Set up a webhook capture for Shopify orders."
  • "Run a health check on my acme/postgres-prod capture."
  • "My capture is failing with an SSH tunnel error. Help me debug it."
  • "Restart the materialization to BigQuery."

For docs-aware Q&A from the same assistants (without the action skills), see MCP Integration.