Statable Analytics

list_sites

Read-only

List the sites this API key can read. Response: {"sites":[{"site_id":123,"name":"<as entered by the owner — often a full URL like https://example.com/>","hash":"07k1eD84d2","timezone":"Europe/Amsterdam","hobby":false,"stats_start_date":"YYYY-MM-DD"|null,"created_at":"RFC3339"}]}. hobby=true is a free-plan site: it counts only through the bundled /t/ script get_tracking_snippet returns, so install that snippet verbatim. Use site_id with the other tools. With date_range each site also carries metrics NESTED under stats.metrics (never flat on the site object). Units: visit_duration = average seconds per visit; bounce_rate = percent 0-100; views_per_visit = pageviews/visits ratio; visitors/pageviews/visits = counts. Stats period boundaries are server-time approximations; use query_stats for timezone-exact numbers.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`date_range`	No	Optional. "7d"/"30d"/"month"/"realtime" or "Nd" for the last N days (1-90), e.g. "7d". Each site then gets {"stats":{"date_range":"7d","metrics":{"visitors":N,"pageviews":N,"visits":N,"visit_duration":seconds,"bounce_rate":percent0to100,"views_per_visit":ratio}}}.

TDQS

A4.9/5.0

Behavior5/5

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

Annotations only provide readOnlyHint, so the description carries the full burden. It discloses response structure, hobby-plan counting limitations, nested metrics behavior, units, and timezone approximations. This is far beyond what readOnly can 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?

Every sentence earns its place: purpose, response example, hobby caveat, downstream usage, nested-metrics warning, unit definitions, and timezone boundary caveat. The content is dense but well-structured and front-loads the core purpose and output.

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

Completeness5/5

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

With no output schema, the description compensates by providing a full response example, unit definitions, and edge-case behavior. Nothing needed to correctly invoke the tool or interpret its result is missing.

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

Parameters4/5

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

The schema description already covers 100% of date_range, so the baseline is 3. The description adds meaning by emphasizing that metrics are nested under stats.metrics (never flat), and by warning that time boundaries are server-time approximations requiring query_stats for exact values. This adds behavioral nuance not present in the schema.

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

Purpose5/5

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

Description states a specific verb ('List'), resource ('sites'), and scoping condition ('this API key can read'), which clearly identifies the operation. The resource differntiation from sibling tools like list_funnels and list_goals is implicit but sufficient.

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

Usage Guidelines5/5

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

Provides explicit when-to-use context: date_range behavior, how to use returned site_id with other tools, and when to prefer query_stats for timezone-exact numbers. It also gives actionable guidance for hobby sites. This is strong routing and alternative-avoidance information.

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

A3.7/5.0

Disambiguation4/5

Most tools map cleanly to distinct resources and actions: sites, goals, funnels, tracking settings, filters, and statistics. Some ambiguity exists between the generic query_stats and the many top_* / visitors_over_time convenience queries, but the descriptions mostly clarify when each should be used.

Naming Consistency3/5

The CRUD tools consistently use create_, get_, list_, and update_ prefixes, but a sizable minority deviate: top_* forms a separate pattern, and current_visitors, funnel_report, and visitors_over_time are noun-phrase names rather than verb_noun.

Tool Count3/5

25 tools sits at the heavy end for an analytics server. Many top_* tools overlap with what query_stats could do, making the count feel somewhat inflated, though the domain is broad enough that the number is not unreasonable.

Completeness3/5

The tool set covers site management, goals, funnels, tracking, filters, and statistics well. However, there are no delete operations for sites, goals, or funnels, leaving an obvious lifecycle gap and no way to clean up configured resources.

Resources

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