apunkt/ktx
1
0
Fork 0
mirror of https://github.com/Kaelio/ktx.git synced 2026-06-13 08:15:14 +02:00
Code Issues Projects Releases Packages Wiki Activity

docs: clarify getting started introduction

Browse source
This commit is contained in:
Luca Martial 2026-05-16 10:24:53 -07:00
parent 68628832a9
commit f8b281b3c4
3 changed files with 167 additions and 69 deletions
Download patch file Download diff file Expand all files Collapse all files

47
docs-site/content/docs/getting-started/introduction.mdx
View file

@ -1,6 +1,6 @@
---
title: Introduction
description: How KTX gives analytics agents trusted context for warehouse work.
description: What KTX is, how it works, and where to start.
---
import { ProductMechanics } from "@/components/product-mechanics";
@ -23,29 +23,39 @@ import { ProductMechanics } from "@/components/product-mechanics";
Make analytics context usable by agents
</h1>
<p className="mt-4 max-w-2xl text-lg text-fd-muted-foreground" style={{ lineHeight: '1.7' }}>
{'KTX turns warehouse metadata, semantic definitions, and business knowledge into reviewable project files that agents can use while planning, querying, and updating analytics work.'}
{'KTX turns warehouse metadata, semantic definitions, BI usage, and team knowledge into local files and runtime tools that database agents can trust.'}
</p>
</div>
</div>
## Why KTX
- Schemas show columns, not business rules.
- Agents need trusted metrics, joins, filters, caveats, and provenance.
- KTX captures that context before agents write SQL, docs, or semantic edits.
## What KTX creates
| Path | What it gives agents |
|------|----------------------|
| `semantic-layer/` | Measures, dimensions, joins, grain, filters, segments |
| `wiki/` | Business definitions, caveats, policies, analyst notes |
| `raw-sources/` | Extracted metadata, scan output, relationship evidence |
| `.ktx/` | Local indexes, embeddings, setup state, runtime data |
<ProductMechanics />
## What agents can do with KTX
KTX is built for analytics engineers and data teams who want data agents to
work on real analytics systems, not just generate one-off SQL.
Use it when agents need to:
## Use it for
- **Generate SQL** from approved measures, dimensions, joins, and filters
- **Explain provenance** with wiki context and warehouse evidence
- **Repair context** through reviewable YAML and Markdown diffs
- **Work alongside** dbt, LookML, MetricFlow, Looker, Metabase, and warehouses
KTX works with SQLite, PostgreSQL, Snowflake, BigQuery, ClickHouse, MySQL, and
SQL Server.
Databases: SQLite, PostgreSQL, Snowflake, BigQuery, ClickHouse, MySQL, SQL
Server.
## Read next
## Start here
<Cards>
<Card title="Quickstart" href="/docs/getting-started/quickstart">
@ -60,16 +70,7 @@ SQL Server.
<Card title="CLI Reference" href="/docs/cli-reference/ktx-setup">
Complete flag and subcommand reference for every KTX command.
</Card>
<Card title="AI Resources" href="/docs/ai-resources">
Machine-readable docs and agent-facing setup notes.
</Card>
</Cards>
## Agent usage notes
| Agent task | Read next |
|------------|-----------|
| Discover machine-readable docs | [AI Resources](/docs/ai-resources) |
| Learn how a coding assistant should approach KTX | [Agent Quickstart](/docs/ai-resources/agent-quickstart) |
| Set up a new KTX project | [Quickstart](/docs/getting-started/quickstart) |
| Explain what problem KTX solves | [The Context Layer](/docs/concepts/the-context-layer) |
| Scan a database and ingest metadata | [Building Context](/docs/guides/building-context) |
| Edit semantic sources or wiki pages | [Writing Context](/docs/guides/writing-context) |
| Look up exact command flags | [CLI Reference](/docs/cli-reference/ktx-setup) |