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Statable Analytics

by com.statable.mcp

top_custom_events

Read-only

Top custom events (data-statable-event) by count for a site — pageview/engagement excluded. Returns {"results":[{"dimensions":{"event:name":"Signup"},"metrics":{"events":N,"visitors":N}}]}, where events is the raw occurrence count and visitors is unique users who triggered it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteNoNumeric site_id (preferred, from list_sites) or a domain, e.g. example.com — scheme, www. and path are ignored when matching. If several sites share the domain the call fails and lists their site_ids. Omit for a single-site key.
limitNoDefault 100, max 1000.
periodNo"7d"/"30d", or any "Nd" = last N full days (N = 1..90); "month" = current calendar month to date. Default 30d.

TDQS

A4/5.0
Behavior4/5

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

The description explains the output format in detail, including the meaning of 'events' and 'visitors', and notes that pageview/engagement are excluded. This provides transparency beyond the schema. However, it does not mention any potential side effects or error scenarios, though the readOnlyHint annotation covers safety.

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 concise and well-structured, presenting the output example and metric definitions in a single sentence. It avoids unnecessary verbosity while conveying essential information effectively.

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 absence of an output schema, the description provides a concrete example and explains the metrics. It covers the key aspects an agent needs to understand the response. It might be improved by mentioning potential error conditions or limits, but for the given complexity, it is fairly complete.

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?

The description does not discuss parameters at all. The schema already provides full coverage for site, limit, and period, each with descriptions. Since schema coverage is 100%, the description adds no extra parameter semantics, warranting the baseline score.

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?

The description clearly states the tool's purpose: 'Top custom events by count for a site' and explicitly excludes 'pageview/engagement'. This distinguishes it from sibling tools like top_pages and top_sources, making the intent unambiguous.

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

Usage Guidelines3/5

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

The description does not explicitly state when to use this tool versus alternatives. It implies usage for retrieving custom event counts, but there is no direct guidance on choosing it over other top_* tools. The context from the sibling list helps, but it's not explicit.

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