Start here: learn the model
If you don’t already know the vertical’s data model, do not call brand tools blind. Learn it first:1
vertical__vertical_legend
Returns the live data model — channels, the signal catalog and what each signal means, example questions, benchmarks, lookups, and live coverage / counts. This is your map.
2
vertical__vertical_knowhow
Returns the getting-started guidance and agent rules — the playbook and method for reasoning over this vertical.
Route by question
For any brand, resolve first.
vertical__vertical_resolve turns a brand name into the canonical entity the other tools expect — never hand-type a brand id into a card or compare call.Grounding rules
These are what separate a grounded market answer from a plausible-sounding guess. Promote them in every response:- Check
data_coveragebefore advising on a brand — thin coverage means a weaker claim. - Don’t invent missing statistics. If a number isn’t in the data, say so.
- Brand-specific numbers beat generic best practice — a retrieved figure outranks a rule of thumb.
- Ground recommendations in retrieved signals, not prior assumptions.
- Distinguish facts from estimates explicitly.
- Don’t fabricate exact rankings from quartile or band signals — a band is a band, not a rank.
- If the dataset lacks a requested fact, say so rather than filling the gap.
Answer shape
Frame market answers as a chain the user can audit:Your data shows X → the playbook says Y → therefore Z.That keeps the retrieved evidence, the method, and the recommendation visible and separable.
Naming & counts
Never hard-code dataset counts or coverage numbers.vertical__vertical_legend reports them live and is the authoritative source — read them at the time you answer, don’t carry a remembered figure.
See Vertical for the complete tool list and parameters, and Routing for how market intelligence fits the wider tool map.