Quattr

describe_data_sources

Read-only

List the data sources available to this account — search performance (default and BigQuery-backed), web analytics, paid search, market share, AI visibility, page experience — with each source's latest available data date, load cadence, and load health. available is entitlement (is the source connected). health is load freshness: current, delayed, stale (stalled feed — flag as broken), unknown, or unavailable. Call this before choosing a source or when data seems missing.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "describe_data_sources"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 19, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the bar is lower. The description adds real value by defining the semantics of the returned fields — available as entitlement, health as load freshness with enumerated states (current/delayed/stale/unknown/unavailable) and an instruction to treat stalled feeds as broken.

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?

Front-loaded with the core action, then the category list, then the field semantics, then the call trigger. Information-dense with no filler, though the parenthetical enumerations make it fairly long.

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 carries the burden of explaining return values, and it does so by defining available and health and their possible states. Nothing an agent needs to call this correctly or interpret the 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 tool takes no input parameters, so the baseline is 4. The description correctly spends no words on arguments and instead documents the output fields.

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?

States a specific verb (List) and resource (data sources available to this account), then enumerates the concrete source categories returned. An agent can distinguish this catalog tool from siblings like get_data_freshness or search_performance without opening any schema.

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?

"Call this before choosing a source or when data seems missing" gives explicit trigger conditions. It stops short of naming the alternative tool to use for per-source drilldown, but the when-to-use guidance is unambiguous.

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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