Maxed Marketing

A time series of a measure, bucketed by interval — counts by default, or sum:/avg: of a declared metric (e.g. "avg:durationMs"). Use for "is this rising?" questions.

A cohort funnel over lifetime milestone families: stage counts, conversion %, drop-off, and median time-to-step. Pass ordered stage families; the cohort window is the time range.

The distinct values present in one column of one marketing table, up to 50. Use when you need to know what categories exist before filtering on them.

Read Maxed's internal engineering and product documentation — architecture, data pipeline, data catalog, AI-visibility and marketing product guides, vendor field references, and administration. Call with NO arguments first to get the index: a table of contents naming every page by its `path`. Then call again with `path` set to one of those values (e.g. "ai-visibility/product/dashboard.md") to read that page's full markdown. Pass `full: true` with no `path` to get the entire corpus in one document.

The full step-by-step playbook for one marketing job. Use the exact key from list_playbooks. Returns current methodology — follow it, using the marketing data tools for this account's real numbers.

Every record sharing one traceId, on a single time axis — the correlated view of one request across services. Get a traceId from search_events or list_errors.

List the Maxed accounts this user can read, with their ids and names. Call this first: every data tool needs an account id, and a user may have several.

Recent error records, newest first — the focused feed for "what is breaking?". A convenience over search_events with kind pinned to "error"; still accepts name/service/env/severity filters.

List the marketing data tables available to query — ad platforms, analytics, search, social and ecommerce — with a one-line description of each. Call this before writing SQL, then describe_marketing_table for the fields.

List Maxed marketing playbooks — step-by-step methodologies for common marketing jobs (paid ads investigation, performance review, boss report, creative brief, breakout-post ideation, …). Call this to find the right playbook for the user's task, then get_playbook for the full instructions.

The menu of reports available in this instance: saved (built by people), configured (wired by the host), and registry-derived. Each has a name and a stored query you can run with run_report.

The tenant roster with recent activity — tenants that emitted anything in the range, each with a rollup-doc count, family count, event total, and last-activity time. Cross-tenant under a platform ("*") viewer; a single row otherwise.

Percentiles (p50/p90/p95/p99), min/max/avg, and a 20-bucket histogram of a numeric metric over the matched records — e.g. "what is p95 latency for the checkout span?". Defaults to durationMs.

Run a read-only BigQuery SELECT against the marketing tables for one account. Use the VIRTUAL table names from list_marketing_tables — never a project.dataset.table path. The account filter is resolved and applied for you; do not add one. Queries against date-partitioned tables must include a date filter. Results are capped at 100 rows unless the query sets its own LIMIT.

Top rows of a pre-aggregated rollup family — top issues, top spenders, most-active accounts, whatever the registry declares. Name the family (`as`) from describe_telemetry; optionally slice by dimension values.

Execute one named report from list_reports and return its result. Read-only: the report is a stored filter/range that dispatches to the same query the dashboard would run.

Raw telemetry records matching a filter, newest first, cursor-paged. The general list/table/tail tool across every kind. `data` payloads are redacted by default.

The health of the telemetry pipeline itself: drop/default/cap counters, quarantined failed writes, and the index budget. Answers "are we silently dropping events?".

One subject's whole story over a range — records interleaved with lifetime milestones. Pass a subject ref like "user:u_1".