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lpicci96

unesco-mcp

by lpicci96

get_country_ranking

Retrieve top and bottom country rankings for a UNESCO UIS indicator. Uses dense ranking to show tied countries at the same rank for a specific year.

Instructions

Rank countries (not regions) by their value for a UNESCO UIS indicator.

Returns the top-N and bottom-N countries for a given indicator in a specific year. Uses dense ranking (tied countries share the same rank).

Year handling:

  • strict_year=True (default): year must be provided explicitly.

  • strict_year=False and year omitted: uses the year with the most country coverage.

Args: indicator_code: The indicator code (e.g. "LR.AG15T99"). year: Optional. The year to rank countries for. If omitted, the year with the most data points is used only when strict_year=False. top_n: Number of top-ranked countries to return (default 10, max 200). bottom_n: Number of bottom-ranked countries to return (default 10, max 200). strict_year: If True, require an explicit year to avoid implicit year selection.

Returns: A dictionary with: - "indicator_code", "indicator_name": Indicator identity. - "year_used": The year the ranking is based on. - "total_countries_with_data": Countries with non-null values that year. - "top": [{rank, code, name, value}, ...] — highest-value countries. - "bottom": [{rank, code, name, value}, ...] — lowest-value countries. - "note": Context (e.g. year selection rationale, overlap explanation).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indicator_codeYes
yearNo
top_nNo
bottom_nNo
strict_yearNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description sufficiently discloses behavior: it returns top and bottom lists, uses dense ranking, and explains year handling. It does not mention read-only nature, but the lack of destructive hints is acceptable for a ranking operation.

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 well-structured with a summary, year handling, Args, and Returns sections. It is front-loaded but slightly verbose; the Args section repeats parameter types already in schema, but adds necessary behavioral context.

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?

Given 5 parameters, no annotations, and an output schema, the description is complete: it covers return fields (indicator info, year, top/bottom with rank, code, name, value) and edge cases (year selection, strict_year).

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

Parameters5/5

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

Schema coverage is 0%, but the description fully explains each parameter (e.g., indicator_code example, strict_year interaction, max for top_n/bottom_n), adding significant 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 clearly states the tool ranks countries by indicator value, specifying the resource (countries vs regions) and the action (ranking). It distinguishes from siblings like 'compare_geographies' or 'get_latest_value' by focusing on ranking for UNESCO UIS indicators.

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 includes detailed usage guidance (e.g., dense ranking, strict_year behavior, parameter defaults) but does not explicitly compare to sibling tools or state when not to use it. However, the clarity of the parameter explanations compensates.

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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