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See Chat with your Co-founder for the conceptual overview.

POST — ask a question

Body: Response:

What happens during a turn

The agent answers with the latest briefing, your memory facts, and semantically-matched past episodes in context. On top of that it has a live tool belt (up to 5 tool steps per turn):
  • Keyword ranks & suggestions, competitor lookups, ASO score
  • App Store Connect metrics, reviews, subscription data
  • Apple Search Ads and RevenueCat summaries
  • Your pending action queue — including approve/reject by id when you explicitly ask
Because tool calls hit live data, a data-heavy turn can take 15–60 seconds. Plan client timeouts accordingly (we recommend ≥120s).

GET — list past Q&A

Response:

Cost

The model comes from your LLM settings (provider + BYOK key, or platform defaults). Typical cost per turn is 0.00050.0005–0.005 depending on model and how many tools the agent used.

Scope and limits

  • Always scoped to your owner_email — the agent can never see another user’s data.
  • The agent can approve/reject existing proposed actions, but cannot originate new write actions from chat — those come from the regular run pipeline with the usual review flow.
  • For a full re-analysis (fresh collector pass), trigger a run instead.
  • For “why did metric X move?” investigations with ranked root causes, use the Why-agent.