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https://github.com/Kaelio/ktx.git
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docs: add agent setup prompt endpoint (#142)
* docs: add agent setup prompt endpoint * docs: wrap agent setup prompt * docs: restyle agent setup note * docs: make agent setup prompt copyable * docs: update quickstart demo callout * docs: align prompt copy button
This commit is contained in:
parent
56f4f9c9e8
commit
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5 changed files with 271 additions and 4 deletions
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@ -3,6 +3,11 @@ import {
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getLlmDocsPages,
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getPageMarkdown,
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} from "@/lib/llm-docs";
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import {
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agentSetupSlug,
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isAgentSetupSlug,
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readAgentSetupMarkdown,
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} from "@/lib/agent-setup-markdown";
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export const dynamic = "force-static";
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@ -11,6 +16,14 @@ export async function GET(
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props: { params: Promise<{ slug?: string[] }> },
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) {
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const params = await props.params;
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if (isAgentSetupSlug(params.slug)) {
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return new Response(await readAgentSetupMarkdown(), {
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headers: {
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"Content-Type": "text/markdown; charset=utf-8",
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},
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});
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}
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const page = getLlmDocsPage(params.slug);
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if (!page) {
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return new Response("Documentation page not found.\n", {
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@ -29,5 +42,8 @@ export async function GET(
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}
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export function generateStaticParams() {
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return getLlmDocsPages().map((page) => ({ slug: page.slug }));
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return [
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...getLlmDocsPages().map((page) => ({ slug: page.slug })),
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{ slug: [...agentSetupSlug] },
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];
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}
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194
docs-site/content/agents-setup.md
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194
docs-site/content/agents-setup.md
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@ -0,0 +1,194 @@
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# Goal
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Set up KTX from scratch end-to-end as a fully autonomous, agent-driven replacement for the interactive `ktx setup` wizard. Detect the environment, install missing prerequisites, ask the user only for information you genuinely need (which connections to add, credentials), write a valid configuration, verify it works, and run a fast schema ingest. Keep the user updated throughout.
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# Operating principles
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- **Be autonomous.** Detect, decide, and act. Only ask the user when you need information that only they can provide: project location, which databases/sources to connect, credentials, and similar choices.
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- **Stream short status updates.** Before each major phase ("Checking prerequisites…", "Installing uv…", "Configuring warehouse connection…", "Running fast ingest…") print a one-line update. Not chatty — just enough that the user can see what's happening.
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- **Verify against docs, never guess.** CLI flags, config keys, and command names must come from the docs or from `ktx <command> --help`. If something looks wrong or missing, say so explicitly.
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- **Print every command you run and its exit code.** Terse, not silent.
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- **Fail loudly with cause + fix.** When a command fails: capture the exact error, identify the cause, change something, retry. Never retry an unchanged command. Exceptions for *known soft-failures* are listed in Phase 4 — handle those without retrying.
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- **No LLM-based ingestion in this flow.** Only `--fast` ingest (schema-only). The user can run `--deep` later.
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- **Platform-agnostic.** Detect the host OS first and pick the right install commands / path syntax. Anything path- or shell-specific must branch on OS.
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# Authoritative docs
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KTX docs are served at `https://docs.kaelio.com/ktx/`. **Start by fetching `https://docs.kaelio.com/ktx/llms.txt`** to discover the docs map. Scan it for a "troubleshooting" entry — if one exists, read it **before** running install/setup so you can apply known fixes preemptively rather than after failing. If no troubleshooting page is listed (current state of the docs), proceed. Then fetch any other `.md` pages you need (setup, ingest, status, connection types). **Never invent CLI flags or config keys** — verify against the docs or `ktx --help` / `ktx <subcommand> --help`.
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> **Note on the `ktx status` JSON example in the docs.** The docs page for `ktx status` shows an example shaped like `{"title": "...", "checks": [...]}`. That example is outdated. The real CLI output uses a top-level `verdict` field plus a `connections[]` array — see Phase 5 for the canonical success criteria. Trust the shape in this prompt over the docs example.
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# Workflow
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## Phase 1 — Detect environment
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Determine the host OS (e.g. via `uname -s`, `process.platform`, or `$env:OS`). Use the right install commands per OS for the rest of this flow.
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| Tool | macOS / Linux | Windows (PowerShell) |
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|------|---------------|----------------------|
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| `uv` | `curl -LsSf https://astral.sh/uv/install.sh \| sh` then re-source shell env | `irm https://astral.sh/uv/install.ps1 \| iex` |
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| Node.js | use system / fnm / nvm — **do not** auto-install | use system / nvm-windows — **do not** auto-install |
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| KTX CLI | `npm install -g …` (see Phase 2) | `npm install -g …` (see Phase 2) |
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If Node.js is missing, **stop and ask the user** to install it (https://nodejs.org/). Do not attempt to auto-install Node.
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## Phase 2 — Verify and install prerequisites
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Check each tool in order; install only if missing.
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1. **Node.js** — run `node --version`. Require >= 22. If missing or older, stop and instruct the user.
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2. **`uv`** — run `uv --version`. If missing, run the OS-appropriate install command, then re-source the shell environment (`export PATH="$HOME/.local/bin:$PATH"` on Linux/macOS) so `uv` is on `PATH`.
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3. **KTX CLI** —
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- Install ktx with `npm install -g @kaelio/ktx`
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- Verify with `ktx --version`.
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Print one status line per tool ("✓ uv 0.11.15 found", "Installing uv…", "✓ ktx 0.x.y installed").
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## Phase 3 — Gather user choices
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Ask the user (grouped if your harness supports it; otherwise sequentially):
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1. **Project directory.** Default: current working directory. Confirm before continuing.
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2. **LLM provider.** Default: `claude-code` with model `sonnet` (the user is already inside Claude Code; no extra API key needed). Offer `anthropic` (paste API key, stored as `env:` or `file:` ref) and `vertex` (GCP project + location) as alternatives. Skip if defaults are accepted.
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3. **Embeddings backend.** Default: `sentence-transformers` (local, no API key, managed Python runtime). Offer `openai` only if the user has a key.
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4. **Database connections.** Ask how many to add, then loop. For each, collect:
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- Connection name (e.g. `warehouse`, `analytics`).
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- Driver: one of `sqlite`, `postgres`, `mysql`, `clickhouse`, `sqlserver`, `bigquery`, `snowflake`.
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- Connection URL/DSN (or service-account file for BigQuery). Accept `env:VAR_NAME` or `file:/abs/path` to avoid pasting raw secrets.
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- **Heads-up for the user**: even if they paste a literal URL, KTX will silently relocate it into `<project>/.ktx/secrets/<connection>-url` and rewrite `ktx.yaml` to `url: file:…` — this is correct, secure behavior and not a bug.
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- Schemas / datasets to include (postgres / sqlserver / snowflake / bigquery only).
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- Optional `enabled_tables` allowlist if the user wants to scope ingest to specific tables.
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5. **BI / metadata sources** (dbt, Metabase, Looker, LookML, MetricFlow, Notion). Default: none. Ask only if the user mentions them.
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## Phase 4 — Configure the project
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Drive the existing wizard non-interactively (verify exact flag names with `ktx setup --help` and the docs — the automation flags are hidden from help but accepted):
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```
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ktx setup \
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--project-dir <path> \
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--new \
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--no-input --yes \
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--llm-backend <claude-code|anthropic|vertex> --llm-model <model> \
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[--anthropic-api-key-env ANTHROPIC_API_KEY | --anthropic-api-key-file <path>] \
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[--vertex-project <p> --vertex-location <loc>] \
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--embedding-backend <sentence-transformers|openai> \
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[--embedding-api-key-env OPENAI_API_KEY] \
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--skip-sources \
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--database <driver> --new-database-connection-id <name> --database-url <url|env:VAR|file:/path> \
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[--database-schema <schema> …]
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# repeat the --database / --new-database-connection-id / --database-url / --database-schema block per connection
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```
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Notes on the flags above:
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- **`--new`** is required when bootstrapping an empty directory; use `--existing` instead when re-running setup against a project that already has a `ktx.yaml`.
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- **There is no `--skip-agents` flag.** The agent integration step is opt-in: setup leaves it alone unless you pass `--agents --target <target>`. So you do not need to skip it — just don't pass `--agents`.
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- **`--skip-sources`** is correct and is the documented way to leave BI/metadata sources unconfigured.
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### Known soft-failure: `ktx setup` exits 1 after a successful fast build
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When you select a configuration that only does fast (schema-only) ingest, `ktx setup`'s final readiness verification fails with:
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```
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KTX context build did not pass agent-readiness verification.
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<connection>: deep database context has not completed.
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```
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This is **expected** and **does not mean setup failed**. Treat the exit code as a soft-failure **only if all of the following hold**:
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- The build log shows the fast ingest reached `[100%] Scan completed` for every configured connection.
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- `ktx connection test <name>` (run next) exits 0 for every connection.
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- `ktx status --json --no-input` reports `verdict: "ready"`.
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If those three conditions hold, proceed to Phase 5 without retrying setup, and **do not** switch to `--deep` to "fix" the readiness gate — deep ingest is explicitly out of scope. Mention this in the final report under "Docs / CLI gaps" so the user is aware.
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If any of those three conditions do not hold, this is a real failure — capture the error, fetch the relevant docs page, fix the cause, retry.
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After `ktx setup` writes `ktx.yaml`, edit it directly for anything flags don't cover:
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- Per-connection `enabled_tables` allowlist (snake_case, under `connections.<name>.enabled_tables`).
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- Any advanced settings the user requested.
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Use a YAML-aware editor (e.g. `uv run python -c "import yaml; …"`) — do not hand-edit blindly.
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## Phase 5 — Verify
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`ktx setup` already runs a fast schema ingest of every database connection it configures, so you do not need to re-ingest by default. For each configured connection:
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```
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ktx connection test <connection-name> # must exit 0
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```
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Only re-run ingest if setup's build log did **not** reach 100% for that connection:
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```
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ktx ingest <connection-name> --fast --no-input
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```
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**Mutex warning on `ktx ingest`**: passing both `--yes` and `--no-input` fails with `Choose only one runtime install mode: --yes or --no-input`. Setup already installed the managed Python runtime, so pass **only `--no-input`** to `ktx ingest`. (`--yes` is only needed when an ingest invocation has to install the runtime itself, which is not the case here.)
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Then run the global health check:
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```
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ktx status --json --no-input
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```
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Success requires (canonical shape — supersedes the example in the docs):
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- `verdict: "ready"` at the top of the JSON.
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- Every `connections[].status === "ok"`.
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- `ktx connection test <name>` exited 0 for every connection.
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Do **not** run `--deep` ingest in this flow — that requires LLM time and is out of scope.
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### Optional: directly probe the embeddings daemon
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If the user asks for stronger verification that `sentence-transformers` is actually serving (not just that setup said "ok"), do all of:
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1. `ktx dev runtime status --json` → expect `"kind": "ready"` and `"features": [..., "local-embeddings"]`.
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2. `pgrep -fa ktx-daemon` → expect a process running `ktx-daemon serve-http`.
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3. `curl -sS http://127.0.0.1:<port>/health` → expect HTTP 200 with `{"status":"healthy",…}`.
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4. `curl -sS -X POST http://127.0.0.1:<port>/embeddings/compute -H 'content-type: application/json' -d '{"text":"hello"}'` → expect `{"embedding": [...384 floats...]}`.
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Discover the port from setup's log line `Started KTX local embeddings daemon: http://127.0.0.1:<port>` or from the daemon's OpenAPI at `GET /openapi.json`. Note: the routes are `/health` and `/embeddings/compute` — not `/healthz` or `/embeddings`.
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## Phase 6 — Final report
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Print a structured report:
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```
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KTX SETUP COMPLETE
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Project: <path>
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LLM: <backend> / <model>
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Embeddings: <backend> / <model>
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Runtime: managed Python ✓ (if sentence-transformers daemon was started)
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Connections:
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- <name> (<driver>) status=ok schemas=[…] tables=<N>
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- …
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Sources: <list or "none">
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Verdict: ready
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```
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Then **Next steps** (copy-pasteable):
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1. Enrich with AI descriptions and embeddings: `ktx ingest <connection> --deep` (several minutes per connection).
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2. Add more connections later by rerunning this setup or via `ktx setup --existing --database … --new-database-connection-id …`.
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3. Configure BI sources (dbt, Metabase, Looker, LookML, MetricFlow, Notion) — see `ktx setup --help` for `--source …` flags.
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4. Install agent integration: `ktx setup --agents --target <claude-code|claude-desktop|codex|cursor|opencode|universal>` (with optional `--global` for `claude-code`/`codex`).
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5. Connect the agent / MCP: see docs at `https://docs.kaelio.com/ktx/`.
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Under **Docs / CLI gaps to flag** include any of these that applied during your run:
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- `ktx setup` exits non-zero after a successful fast build (deep-readiness gate); status reports ready.
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- `ktx ingest` rejects `--yes` and `--no-input` together; docs don't note the conflict.
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- `ktx status --json` real shape (`verdict`, `connections[]`) doesn't match the example in the docs page.
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- The pasted DB URL was moved to `.ktx/secrets/<name>-url` automatically.
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End with a single line: `RESULT: PASS` or `RESULT: FAIL — <one-line reason>`.
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# Operating rules (recap)
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- Print every command you run and its exit code. Status updates may be terse, but never silent.
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- On failure: capture the error, fetch the relevant docs page, fix the cause, retry. Never retry an unchanged command.
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- Known soft-failures (listed in Phase 4 and Phase 5) are not real failures — handle them as documented; do not retry or escalate.
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- If you find a docs/CLI gap ("docs say X but CLI does Y"), call it out in the final report.
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- Never commit credentials — KTX accepts `env:` and `file:` references; prefer those. KTX will also auto-relocate literal URLs into `.ktx/secrets/`, but that does not protect anyone who pasted the URL into chat history.
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@ -3,6 +3,8 @@ title: Quickstart
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description: Install KTX, run setup, and connect your coding agent.
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---
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import { CopyButton } from "@/components/copy-button";
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This guide takes a local analytics project from empty to agent-ready. You'll
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install the CLI, run one guided setup command, and hand the context to a
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coding assistant.
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@ -11,10 +13,9 @@ If you're a coding assistant choosing a docs route, start with the
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[Agent Quickstart](/docs/ai-resources/agent-quickstart) instead.
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<div
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className="not-prose my-8 rounded-xl border border-l-4 p-5 sm:p-6"
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className="not-prose my-8 rounded-xl border p-5 sm:p-6"
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style={{
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borderColor: 'color-mix(in oklch, #ff8a4d 35%, transparent)',
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borderLeftColor: '#ff8a4d',
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background: 'color-mix(in oklch, #ff8a4d 8%, transparent)',
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}}
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>
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@ -22,7 +23,7 @@ If you're a coding assistant choosing a docs route, start with the
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className="text-xs font-semibold uppercase tracking-wider"
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style={{ color: '#ff8a4d' }}
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>
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No warehouse handy?
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Need a warehouse to play with?
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</div>
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<div className="mt-2 text-base leading-relaxed text-fd-foreground">
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Try KTX against a real data stack - Postgres, dbt, Metabase, and Notion
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@ -41,6 +42,49 @@ If you're a coding assistant choosing a docs route, start with the
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</a>
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</div>
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<div
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className="not-prose my-6 rounded-lg border p-4"
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style={{
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borderColor: 'color-mix(in oklch, var(--color-fd-primary) 35%, transparent)',
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background: 'color-mix(in oklch, var(--color-fd-primary) 8%, transparent)',
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}}
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>
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<div className="text-sm font-semibold text-fd-foreground">
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Run setup from an agent
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</div>
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<div className="mt-2 text-sm leading-6 text-fd-muted-foreground">
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You can ask an agent such as Claude Code, Codex, Cursor, or OpenCode to
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install and configure KTX for you. The{' '}
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<a href="/ktx/docs/agents-setup.md" className="font-medium underline">
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agent setup Markdown prompt
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</a>{' '}
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tells the agent how to check prerequisites, ask only for credentials or
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connection choices, run <code>ktx setup</code>, verify connections, and
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report the result.
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</div>
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<div className="mt-3 text-sm leading-6 text-fd-muted-foreground">
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Use a prompt like this from the project you want to configure:
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</div>
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<div className="mt-3 max-w-full overflow-hidden rounded-md border bg-fd-background">
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<div className="flex items-center justify-between gap-2 border-b px-3 py-2">
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<span className="text-xs font-semibold uppercase tracking-wide text-fd-muted-foreground">
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Prompt
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</span>
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<CopyButton
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text={`Follow instructions from
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https://docs.kaelio.com/ktx/docs/agents-setup.md
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to install and configure ktx`}
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className="-my-1"
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/>
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</div>
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<div className="p-3 font-mono text-sm leading-6 text-fd-foreground">
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<div>Follow instructions from</div>
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<div className="break-all">https://docs.kaelio.com/ktx/docs/agents-setup.md</div>
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<div>to install and configure ktx</div>
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</div>
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</div>
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</div>
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## Install the CLI
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Install the published package globally:
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12
docs-site/lib/agent-setup-markdown.ts
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12
docs-site/lib/agent-setup-markdown.ts
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import { readFile } from "node:fs/promises";
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import { join } from "node:path";
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export const agentSetupSlug = ["agents-setup"] as const;
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export function isAgentSetupSlug(slug: string[] | undefined) {
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return slug?.length === 1 && slug[0] === agentSetupSlug[0];
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}
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export function readAgentSetupMarkdown() {
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return readFile(join(process.cwd(), "content/agents-setup.md"), "utf8");
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}
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@ -53,6 +53,7 @@ KTX provides semantic-layer files, warehouse scans, wiki pages, provenance, and
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## Agent Entry Points
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${link("/docs/ai-resources/agent-quickstart", "Agent Quickstart", "Task-first route for coding assistants using KTX")}
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${link("/docs/agents-setup", "Agent Setup", "Copy-pasteable prompt for agents installing and configuring KTX")}
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${link("/docs/ai-resources/markdown-access", "Markdown Access", "Fetch KTX docs as llms.txt, llms-full.txt, or per-page Markdown")}
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${link("/docs/ai-resources/agent-instructions", "Agent Instructions", "Suggested instructions for coding assistants that need to read and cite KTX docs")}
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