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Documentation Index

Fetch the complete documentation index at: https://docs.upstackdata.com/llms.txt

Use this file to discover all available pages before exploring further.

The CLI is intentionally dumb — Claude (or another agent) running in your terminal does the natural-language parsing and constructs structured upstack calls. No LLM ever runs server-side in Upstack.

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Example session

> Claude, make me a dashboard with NC ROAS, MER, and Facebook CPM.

$ upstack measures --search "new customer roas"   # confirms core.new_customer_roas
$ upstack measures --search mer                   # core.new_customer_mer
$ upstack measures --search "facebook cpm"        # meta.cpm
$ upstack dashboard view build \
    --name "NC + Meta Pulse" \
    --measures core.new_customer_roas,core.new_customer_mer,meta.cpm
# → Created dashboard view 5f1e6a4f-... "NC + Meta Pulse" with 3 widget(s).
#   Open the dashboard app and select it from the view dropdown.
The agent picks measure ids using upstack measures, then issues a single build call. Same result as the API quickstart, in one structured command.

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Why this works

  • Discovery is free. upstack measures doesn’t require any special scope. An agent can introspect what’s available before constructing a request.
  • The CLI is structured input for the agent’s structured output. Flags are JSON-shaped (--measures m1,m2,m3, --from-file payload.json). No shell-quoting gymnastics for natural-language prompts.
  • Every command can be replayed. Pass --from-file to load a JSON body, then iterate via flags. The agent doesn’t need to remember state — it can re-issue.

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What the agent should NOT do

  • Don’t ask the user for their API key over chat. Credentials are already in ~/.upstackrc; the CLI handles auth automatically.
  • Don’t hand-construct API request bodies in chat. Use the CLI as the structured interface — it’s already typed and validated.