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Get Data Quality

get_data_quality
Read-onlyIdempotent

Report collector health — coverage, per-source freshness and missed snapshot runs with reasons, separating recent misses from the whole recorded history; internal-only sources are excluded. Read-only aggregation of daily-collected observatory data; no side effects. Use when the user asks whether the observatory data is fresh or complete.

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": "get_data_quality"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/non-destructive, so 'read-only aggregation ... no side effects' is largely redundant. The description does add genuinely new behavioral detail beyond annotations: internal-only sources are excluded from the report, and recent misses are separated from full recorded history.

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?

Two sentences, front-loaded with the report contents and followed by the usage trigger; every clause carries information. The first sentence is dense with em-dash lists but not padded.

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?

With an output schema present, the description needn't explain return values, and it correctly focuses on scope, exclusions, and when to call. It stops short of noting anything about refresh cadence or result size, but for a no-param read-only report tool this is close to complete.

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 zero parameters and the schema is fully described, so there is no parameter meaning to add. Baseline for a 0-param tool is 4; nothing in the description is needed to clarify inputs.

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?

Names a specific verb+resource ('Report collector health') and then enumerates the exact contents: coverage, per-source freshness, missed snapshot runs with reasons. This clearly differs from every sibling, which are domain summarizers (finance, npm, leaderboard, etc.).

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?

'Use when the user asks whether the observatory data is fresh or complete' gives a concrete trigger condition tied to user intent. It doesn't name an alternative tool or state when not to use it, but the sibling list contains no overlapping freshness/health tool, so the routing risk is low.

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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