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Get Source Url Usage Time Series Tool

get-source-url-usage-time-series-tool

Read-onlyIdempotent

For each top URL, the percentage of analyzed responses in the bucket that cited that exact URL. Capped to the top top_n URLs (default 20, max 50).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_id": "<project_id>",
      "start_date": "<start_date>",
      "end_date": "<end_date>"
    },
    "name": "get-source-url-usage-time-series-tool"
  }
}

Input Schema

Name	Required	Description
`tags`	No	Tag IDs (prompt classifiers) to limit responses by. Optional.
`top_n`	No	Cap on series count (default 20, max 50).
`end_date`	Yes	Inclusive UTC end of the analytics window. Must be on or after `start_date` and on or before today.
`interval`	No	Bucket granularity for time-series tools. One of: day, week, month, year. Required for time-series tools, ignored for aggregate tools.
`monitors`	No	Monitor IDs in the active project. Optional.
`countries`	No	ISO-3166-1 alpha-2 country codes to include. Optional.
`platforms`	No	AI platforms to include. Optional. Values: chatgpt, perplexity, gemini, grok, copilot, claude, google_ai_mode, google_ai_overview.
`project_id`	Yes	Project to compute analytics for.
`start_date`	Yes	Inclusive UTC start of the analytics window. ISO 8601 date (YYYY-MM-DD).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 15, 2026

TDQS

A3.5/5.0

Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior, so the safety bar is met without description help. The description adds real value beyond that by disclosing the metric's denominator ('analyzed responses'), the exact-URL matching rule, and the truncation behavior with default 20 / max 50. It does not mention what happens to URLs outside the top_n, but the computation semantics are unusually well disclosed.

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 short sentences, zero filler, with the metric definition front-loaded and the cap constraint second. The leading prepositional phrase is slightly fragment-like but reads cleanly as a definition.

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?

For a read-only time-series metric tool with full schema coverage and annotations, the description covers the calculation and the cap but never states that the output is a per-URL series across interval buckets, nor references interval as required. With no output schema, a sentence on the returned shape would close the remaining gap.

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 coverage is 100%, so the schema already documents all nine parameters, and the description only restates top_n's default and max. The critical time-series parameters (interval, date window, tags/monitors/countries/platforms filters) get no additional narrative meaning. Baseline 3 is appropriate when the schema carries the parameter burden.

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?

The description states a specific metric: per-URL percentage of analyzed responses citing that exact URL, bucketed over time, capped at top_n. It makes the 'exact URL' matching semantics explicit, which is the key differentiator. It does not name or contrast with siblings such as get-source-usage-time-series-tool or list-source-url-analytics-tool, so differentiation is left to inference.

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?

There is no when-to-use or when-not-to-use guidance, no mention of alternatives (e.g., the aggregate list-source-url-analytics-tool vs. this time-series variant), and no stated prerequisites. The agent must infer the call context entirely from the name and the 'in the bucket' phrasing.

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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