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get_top_clicked_urls

Read-only

URLs users actually clicked from inside the embed (search results, citation links, follow-ups, etc.), ranked by click count. Optionally filter by click event type. Use this to see what users find useful enough to click through to.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of rows to return, ordered by count descending.
event_typesNoRestrict to specific click-event type(s): 'search_result', 'link', 'contact', 'tool', 'follow_up_navigation', 'follow_up_question'. Omit to include all.
time_filterNoTime window for the analytics query. Accepts either: (a) a preset enum value: 'this_month', 'this_year', 'last_month', 'last_30_days' (default), 'last_6_months', 'last_12_months'; or (b) an explicit ISO date range as 'YYYY-MM-DD,YYYY-MM-DD' (inclusive).last_30_days

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / event_types / anyOf
      Previous value: -[
-  {
-    "items": {
-      "enum": [
-        "search_result",
-        "link",
-        "contact",
-        "tool",
-        "follow_up_navigation",
-        "follow_up_question",
-        "custom"
-      ],
-      "type": "string"
-    },
-    "type": "array"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "items": {
+      "enum": [
+        "search_result",
+        "link",
+        "contact",
+        "tool",
+        "follow_up_navigation",
+        "follow_up_question",
+        "custom",
+        "analytics"
+      ],
+      "type": "string"
+    },
+    "type": "array"
+  },
+  {
+    "type": "null"
+  }
+]
  2. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so this is known to be a safe read operation. The description adds that results are ranked by click count and represent actual click-through behavior, but it does not go deeper into behavioral details such as aggregation rules or uniqueness of URLs. This is acceptable given the annotation coverage but not exceptional.

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?

The description is concise and front-loaded with the core output and ranking behavior. The 'Use this to...' sentence earns its place by clarifying intent, though the 'Optionally filter by click event type' phrase somewhat duplicates the schema's parameter documentation.

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?

The description is sufficient for a read-only analytics tool with no required parameters and a complete output schema. It explains what is returned, the ranking, and a primary use case. It could explicitly mention the default time window, but that is already covered in the schema.

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 input schema has 100% description coverage, so all three parameters (limit, event_types, time_filter) are already well-documented. The description only restates that event-type filtering is optional, adding no substantial meaning beyond 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?

The description states the exact resource: URLs clicked from inside the embed, and the ranking criterion: click count. It clearly differentiates from siblings like get_top_cited_sources or get_top_searches by emphasizing actual click-throughs from the embed.

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 an explicit use case: 'Use this to see what users find useful enough to click through to.' It does not explicitly name alternatives or when-not-to-use conditions, but the intended context is clear enough for an agent to select it appropriately.

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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