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who-health

Access WHO Global Health Observatory data including health indicators, country statistics, and regional trends using OData API queries for analysis and research.

Instructions

Unified tool for WHO Global Health Observatory operations: access health indicators, country statistics, and regional data via the modern OData API. Provides access to comprehensive health data from the World Health Organization covering topics like life expectancy, disease burden, health systems, and risk factors using standard OData query syntax.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
methodYesThe operation to perform: get_dimensions (list all data dimensions), get_dimension_codes (list codes for a dimension), get_health_data (retrieve indicator data), search_indicators (find health indicators), get_country_data (country-specific data), or get_cross_table (tabular data view)
dimension_codeNoFor get_dimension_codes: The dimension code to retrieve (e.g., "COUNTRY" for countries, "REGION" for WHO regions)
indicator_codeNoFor get_health_data, get_country_data, get_cross_table: WHO health indicator code (e.g., "WHOSIS_000001" for life expectancy)
keywordsNoFor search_indicators: Search terms for finding health indicators (e.g., "life expectancy", "mortality", "diabetes", "vaccination")
topNoFor get_health_data, get_country_data: Maximum number of records to return (OData $top parameter)
filterNoFor get_health_data: OData filter expression to limit results. Supports country/time filtering, disaggregation checks (null/not null), and date functions.
country_codeNoFor get_country_data: ISO 3-letter country code (e.g., "USA", "GBR", "CHN")
region_codeNoFor get_country_data: WHO region code (e.g., "EUR" for Europe, "AMR" for Americas)
yearNoFor get_country_data: Specific year or year range for data (e.g., "2020", "2015:2020")
countriesNoFor get_cross_table: Comma-separated list of country codes to include
yearsNoFor get_cross_table: Year range (YYYY:YYYY) or specific year (YYYY)
sexNoFor get_cross_table, get_country_data: Sex dimension filter
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'Provides access to comprehensive health data' and mentions OData API usage, but fails to disclose critical traits: whether it's read-only or mutative, authentication requirements, rate limits, error handling, or response formats. For a tool with 12 parameters and no output schema, this is a significant gap in transparency.

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 appropriately sized and front-loaded, starting with the unified purpose and key features. Both sentences earn their place by explaining the tool's scope and technical approach. However, it could be slightly more concise by integrating the OData mentions more seamlessly, but overall it's efficient with minimal waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (12 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, usage guidelines, and output expectations, which are crucial for an agent to invoke it correctly. While it covers the purpose and data scope, it doesn't compensate for the missing structured information, leaving significant gaps in understanding.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds marginal value by mentioning 'OData query syntax' and examples of data topics, but doesn't provide additional parameter semantics beyond what's in the schema. This meets the baseline for high schema coverage without compensating with extra insights.

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 clearly states the tool's purpose: 'access health indicators, country statistics, and regional data via the modern OData API' and specifies it's for WHO Global Health Observatory operations. It distinguishes the scope ('comprehensive health data from the World Health Organization') and examples of topics covered. However, with no sibling tools mentioned, it doesn't need to differentiate from alternatives, so it's not a 5.

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?

The description provides no guidance on when to use this tool versus alternatives or any prerequisites. It mentions 'via the modern OData API' and 'using standard OData query syntax,' which gives some technical context, but lacks explicit usage scenarios, exclusions, or comparisons to other methods. This leaves the agent with minimal direction on appropriate application.

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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