Files
lancedb/docs/web/basics/agentic-skills.mdx
T
Jack Ye 4015560b83 docs: restructure around the three API surfaces
The Documentation tab now reads as a manual over Python, TypeScript and SQL
rather than a Python guide with SQL bolted on.

Basics replaces the Catalog section: what the catalog holds, what each API
surface can do, jobs, agentic skills, and what Lance is. Management is new and
is the CRUD and listing reference for every catalog object, with a column per
language so the gaps are visible -- TypeScript has no function or SQL methods,
SQL needs a deployment.

Search becomes Query and gains a SELECT reference, since an analytical query is
a query whether it came from a builder or a statement.

Jobs is new. Every long-running operation already returned the same handle from
an _async method; nothing documented it.

The SQL function reference gains what Lance registers on top of DataFusion:
contains_tokens, backed by the FTS index, and the JSON accessors, backed by a
JSON scalar index. Geospatial st_* functions are behind a build feature LanceDB
does not ship, which is now stated rather than left to a confusing error.

Removes the Geneva pages' orphaned snippets, merges FTS Examples into Full-Text
Search, and splits Query Optimization into Explain and Explain Analyze.
2026-09-09 22:20:19 -07:00

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---
title: "Agentic skills"
sidebarTitle: "Agentic Skills"
description: "Give a coding agent a current, maintained reference for the LanceDB APIs."
icon: robot
keywords: ["agents", "plugin", "claude code", "codex", "cursor", "copilot"]
---
A coding agent writing LanceDB code from memory writes whatever was in its
training data -- often an older API, sometimes one that never existed. The
LanceDB agent plugin fixes that by supplying the current reference at the point
the agent needs it.
## The plugin {#plugin}
It ships as the `lancedb` plugin in the
[lancedb-agent-plugins](https://github.com/lancedb/lancedb-agent-plugins)
repository, which doubles as a plugin marketplace. It covers the Python and
TypeScript APIs, which code is portable between a local database and a
deployment, ingestion performance, and branch operations.
<CodeGroup>
```text Claude Code
/plugin marketplace add lancedb/lancedb-agent-plugins
/plugin install lancedb@lancedb
```
```bash Codex icon="terminal"
codex plugin marketplace add lancedb/lancedb-agent-plugins
codex plugin add lancedb@lancedb
```
```bash Other agents icon="terminal"
npx plugins add lancedb/lancedb-agent-plugins
```
</CodeGroup>
The cross-tool installer detects which agent CLIs are on your `PATH` -- Cursor,
GitHub Copilot CLI, VS Code, Grok Build, Kimi Code, Claude Code, Codex -- and
installs through each one's native plugin system.
## What agents are good at here {#workflows}
Two things about LanceDB make it unusually agent-friendly, and both have a
worked tutorial.
<Columns cols={2}>
<Card title="Build an ingestion pipeline" icon="robot" href="/build-with-ai-agents">
Install the plugin and have an agent build a multimodal ingestion pipeline
end to end.
</Card>
<Card title="Run experiments on branches" icon="flask" href="/agent-branch-experiments">
Isolate agent-driven experiments on a branch, evaluate them on a fixed test
set, and promote only the winner.
</Card>
</Columns>
The second is the more interesting pattern. [Branches](/tables/versioning)
give an agent somewhere to be wrong safely: it can rewrite a schema, recompute a
column, or try three embedding models without touching `main`, and you keep only
what measured better.