Production context / 3 min read

Product analytics your coding agent can actually use

Turn telemetry into queryable agent context—scoped release data and funnels, not chat screenshots.

Illustration for Product Analytics for Coding Agents

Product data preview

Signals to agent context

Funnels, instrumentation, and evidence your coding agent can act on.

Separate release and debug traffic.
Agents query data without burning dashboard seats.

Give your AI coding agent production analytics it can use to find product work based on real funnels, retention, exports, and growth evidence.

Who this is for

Start here if the problem below sounds familiar. You do not need every connector on day one—just enough signal for the Growth Engineer to propose work you can review.

  • Teams using OpenClaw, Codex, Claude Code, or Cursor
  • Products that need evidence on growth tasks
  • Founders who want agents to read real data first

How it works

The loop is the same across guides: connect evidence, let the agent read it, then ship a reviewed task with a verification metric.

  1. Install the SDK and track activation, retention, and monetization events.
  2. Create scoped read-only access for agents.
  3. Combine analytics with revenue, crashes, store, and code context.
  4. Review issues or PR tasks with evidence attached.

What you get back

The output should be concrete enough to review without opening five dashboards.

  • Separate release and debug traffic.
  • Agents query data without burning dashboard seats.
  • SDK supports web, Expo, and React Native.

Common questions

Quick answers before you connect product data to an agent.

Can coding agents query AnalyticsCLI directly?

Yes—via CLI workflows with scoped read-only access.

Does this replace the dashboard?

No. The dashboard is for humans; the CLI gives agents deterministic evidence.

Which agents work with AnalyticsCLI?

OpenClaw, Codex, Claude Code, Cursor, and other CLIs that can run commands.