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get_entity_profile

Read-onlyIdempotent

Retrieve all available indicators and their metadata for any country or aggregate entity. Use entity codes like DEU or WLD to discover metrics and time coverage.

Instructions

Get all indicators available for one entity (country, aggregate, etc.). Returns indicator IDs with metadata + time coverage. Use this to discover what you can query about Germany, USA, G7, or any known entity. Entity IDs are ISO 3166 codes (DEU, USA, CHN) or World Bank aggregates (WLD, EUU, EMU, SSF).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_idYesEntity code (e.g. "DEU" for Germany, "USA" for United States, "EUU" for European Union, "WLD" for World)
topicNoOptional: filter indicators by topic
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds value by stating return content (indicator IDs with metadata and time coverage) and clarifying entity ID standards (ISO 3166 codes or World Bank aggregates), which aids agent understanding without contradicting annotations.

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?

Three concise sentences: purpose, usage guidance, and ID format detail. No filler. The most critical information is front-loaded ('Get all indicators...'), making it easy for an agent to parse quickly.

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?

Given the absence of an output schema, the description adequately summarizes return values (indicator IDs, metadata, time coverage). It doesn't detail the exact structure, but for a discovery tool with simple return types, this is sufficient. Strong enough for an agent to form correct expectations.

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?

Schema has 100% description coverage for both parameters. The description adds context for entity_id by specifying ISO 3166 codes and World Bank aggregates, going beyond the schema's examples. The topic parameter is not elaborated further, but the schema already explains its optional filtering role.

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 specifies a concrete action: 'Get all indicators available for one entity.' It mentions return values (indicator IDs, metadata, time coverage) and distinguishes from siblings like 'get_entity_data' by focusing on discovery rather than data retrieval.

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?

It clearly tells when to use the tool: to discover what indicators exist for an entity. Provides examples (Germany, USA, G7) and entity ID formats. While it doesn't explicitly mention when not to use, the sibling set implies alternatives like 'get_entity_data' for actual values, making the guidance sufficient.

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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