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lbruce-wq

Development Indicators MCP

by lbruce-wq

compare_observations

Retrieve development indicator series for selected countries, compare them side by side, and flag metadata differences without merging the data.

Instructions

Retrieve series side by side and flag obvious metadata differences without merging them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_yearNo
start_yearNo
latest_onlyNo
series_refsYes
country_codesYes
include_originalNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
seriesYes
source_errorsNo
comparability_warningsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It clearly states that the tool retrieves series side by side and does not merge them, which is important non-destructive context. However, it leaves 'obvious metadata differences' undefined and says nothing about permissions, rate limits, or error behavior.

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?

A single, front-loaded sentence conveys the core behavior with no filler. Every phrase ('side by side', 'without merging') adds information.

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?

The output schema covers return values, and the description communicates the main behavior, but the lack of usage guidance and parameter semantics leaves gaps for a six-parameter tool. Required fields like country_codes are not motivated, and no alternative routing is given. Still, the core operation is understandable, so it is minimally viable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description adds no parameter-level meaning beyond what the property names already convey. It does not explain required country_codes or the optional start_year, end_year, latest_only, and include_original parameters, so the agent has to guess their semantics from names and types.

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 names a concrete verb ('Retrieve'), a specific resource ('series'), and the differentiating outcome ('flag obvious metadata differences without merging them'). This makes it easy to distinguish from sibling get_observations, which would just fetch data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for side-by-side comparison, but it never states when to choose compare_observations over get_observations or find_microdata, nor does it list exclusions. There is no explicit 'use this when...' guidance, leaving the agent to infer the intended scenario.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.