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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
NameRequiredDescriptionDefault
toNoISO end, alternative to period
fromNoISO start, alternative to period
siteNothe 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.
limitNomax rows returned (default 50)
metricYeswhat to count
periodNorelative period like '24h', '7d' (default), '4w'
filtersNoequality filters, dimension name -> exact value
dimensionNogroup results by this dimension; omit for a single total

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYes
siteYes
metricYes
periodYes
dimensionYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, and the description's read-style verb ('Break a metric down') is consistent with that, so there is no contradiction. The description adds modest behavioral context by specifying period syntax ('24h'/'7d'/'4w' style, or ISO from/to) and filter semantics, but doesn't disclose limit/pagination behavior or result shape — though an output schema exists to cover the latter.

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

Conciseness4/5

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

One dense sentence front-loads the core operation, followed by compact lists of metrics, dimensions, and period formats. The enum lists are slightly redundant with the schema, but nothing is extraneous and the useful period-format note earns its place.

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

Completeness3/5

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

Given full schema coverage and an output schema, the description need not explain return values or most parameters, and it does cover the core operation and period semantics. The notable gap is the absence of usage guidance relative to the many analytics sibling tools, which matters especially for a tool named as generically as 'query'.

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%, so the schema already documents all 8 parameters; the description mostly re-lists the metric and dimension enums already present in the schema. The only additive tidbit is clarifying the period format and the ISO from/to alternative, which is modest — the baseline 3 for high schema coverage applies.

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?

Opens with a specific verb-resource-scope statement ('Break a metric down by a dimension with optional equality filters') and enumerates the allowed metrics and dimensions. The operation is clear, but it does not explicitly differentiate from analytics siblings like get_overview or funnel, so the agent must infer the boundary.

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

Usage Guidelines2/5

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

No guidance on when to choose this tool over analytics siblings such as get_overview, funnel, journeys, what_broke, or what_changed. No exclusions, prerequisites, or alternatives are mentioned, leaving the agent without routing help beyond the raw sibling names.

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

A3.9/5.0
Disambiguation4/5

Most tools target clearly distinct resources or analytic questions: site CRUD, annotation handling, overviews, funnels, journeys, and diagnostic checks are separated. A few tools like get_overview, query, and what_changed could overlap when asking 'what happened', but their descriptions differentiate the intended use well.

Naming Consistency3/5

The CRUD tools follow a clean verb_noun pattern (create_site, delete_site, list_sites, update_site_context), but analysis tools mix bare nouns (funnel, journeys), bare verbs (query), adverb-verb compounds (compare_around), and what_* question phrases (what_broke, what_changed). Naming is readable and snake_case is consistent, but the overall convention is not uniform.

Tool Count5/5

15 tools is within the well-scoped range and each tool earns its place: site management, annotation tracking, traffic overview, discovery, diagnostics, and comparison all have dedicated tools. There is no obvious redundancy or padding.

Completeness4/5

The surface covers the core domain well: sites can be created, listed, deleted, and contextualized; annotations can be recorded and listed; analytics support overview, breakdown, funnel, journey, and anomaly questions. Minor gaps exist such as no update/delete for annotations and no single-site getter separate from list_sites, but agents can work around these.