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Mini site analytics

get_mini_site_analytics
Read-only

Performance of a bio page: LIFETIME totals for views, clicks, best-performing links, visitor source/device/country and AI-crawler reads, plus which published posts drove clicks (post-to-click attribution) over a configurable recent window. Every figure except the attribution rows is an all-time counter, not a windowed one — say so when reporting numbers. Omit siteId when the team has exactly one site.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteIdNo
attributionDaysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
aiYes
byDeviceYes
bySourceYes
topLinksYes
byCountryYes
attributionYes
viewsAllTimeYes
clicksAllTimeYes
attributionWindowDaysYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description goes well beyond the readOnlyHint/openWorldHint annotations by disclosing a critical data subtlety: all counters are LIFETIME totals except the attribution rows, which use a configurable window. It even instructs the agent to communicate this distinction when reporting, which is high-value behavioral guidance.

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?

Two dense sentences carry substantial information with zero filler. The most important facts—lifetime vs. windowed semantics and the siteId omission rule—are front-loaded and easy for an agent to parse.

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?

For a read-only analytics tool with a full output schema, the description covers the tool's scope, metric semantics, parameter behavior, and a notable edge case. Nothing essential to selecting or invoking the tool 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?

With 0% schema description coverage, the description compensates meaningfully: it explains attributionDays via 'configurable recent window' and clarifies siteId's optionality with the single-site team rule. It could more explicitly define siteId as an identifier of the mini site, but the provided hints are sufficient for correct invocation.

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 unambiguously defines the resource (a bio page / mini site) and enumerates the exact metrics returned: views, clicks, best-performing links, visitor dimensions, crawler reads, and post-to-click attribution. This level of specificity distinguishes it from broader analytics siblings like get_channel_analytics.

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 bio-page framing gives a clear context for when to use this tool, and the note 'Omit siteId when the team has exactly one site' is a concrete usage rule. It does not explicitly name alternatives or when-not-to-use conditions, but the scope is clear enough to route an agent correctly.

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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