Staats

Query metrics

query

Read-only

Break a metric down by a dimension with optional equality filters. Metrics: visitors, pageviews, events. Dimensions: path, referrer_domain, utm_source, utm_medium, utm_campaign, device, browser, os, country, name, day. period: '24h'/'7d'/'4w' style, or ISO from/to.

Input Schema

TableJSON Schema

Name	Required	Description
`to`	No	ISO end, alternative to period
`from`	No	ISO start, alternative to period
`site`	No	the site's data-site code, from its script tag or list_sites. Omit when the account has a single site. In a tracked project, read the code from the script tag before asking the user.
`limit`	No	max rows returned (default 50)
`metric`	Yes	what to count
`period`	No	relative period like '24h', '7d' (default), '4w'
`filters`	No	equality filters, dimension name -> exact value
`dimension`	No	group results by this dimension; omit for a single total

Output Schema

TableJSON Schema

Name	Required	Description	Default
`rows`	Yes
`site`	Yes
`metric`	Yes
`period`	Yes
`dimension`	Yes

TDQS

A3.8/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, covering the safety profile. The description adds useful operation details such as supported metrics, dimensions, and period formats, but it does not disclose additional behavior beyond what annotations and schema already convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, front-loaded with the core action, and every sentence earns its place. The lists of metrics, dimensions, and period styles are dense but directly useful, with no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the rich schema, output schema, and annotations, the description is nearly sufficient for correct invocation. It covers the main options and enums, though it could be stronger by explicitly indicating when a sibling tool like funnel or get_overview would be more appropriate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the description mostly restates enum values and period options that already exist in the schema. It adds no significant new meaning beyond the structured parameter descriptions, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'Break a metric down by a dimension with optional equality filters,' and enumerates valid metrics and dimensions. It is clear about what the tool does, but it does not explicitly distinguish it from sibling analytics tools such as funnel or get_overview.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context: query a metric, optionally group by a dimension, optionally filter by equality, and choose a period. It does not mention when not to use this tool or point to alternatives, so it stops short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4/5.0

Disambiguation5/5

Each tool maps to a distinct resource or action: site management, site context, annotations, overviews, dimensional queries, funnels, journeys, and anomaly checks. Overlapping pairs like funnel/journeys are explicitly disambiguated in the descriptions, and what_broke vs what_changed cleanly separate problems from notable movements.

Naming Consistency3/5

Most tools follow a clear verb_noun pattern such as create_site, list_annotations, and update_site_context, but funnel, journeys, portfolio_overview, what_broke, and what_changed break that pattern. The names are still readable and somewhat grouped by intent, but the mixed conventions make it harder to predict a tool's role from its name alone.

Tool Count5/5

At 15 tools this sits at the upper edge of the ideal range, and each tool earns its place: site lifecycle, context, annotation timeline, core analytics, discovery reports, and post-deploy checks are all covered. There is no obvious redundancy or filler.

Completeness4/5

The set covers site management, context editing, annotations, overview/query/funnel/journeys/portfolio analytics, and what_broke/what_changed checks, so most workflows have no dead ends. Minor gaps exist, such as no way to edit or delete a mistaken annotation and no explicit tool for updating data-retention settings, but these are workaroundable rather than blocking.

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