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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, which cover safety and side effects. The description adds meaningful behavioral context: it bundles multiple indicators into one snapshot, includes both latest and previous values, and provides source and license evidence. This goes beyond the annotations by explaining what the output contains. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that packs a lot of information: the exact indicators, the normalization, the temporal scope (latest and previous), and evidence inclusion. It is concise and front-loaded, but it is somewhat long and could be broken into two sentences for clarity. Still, every phrase adds value, so a 4 is appropriate.

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

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

Given the tool has an output schema (though not shown), annotations that establish read-only/open/idempotent behavior, and a clear parameter list, the description is largely complete. It explains what data is bundled and that evidence is attached. It could specify whether 'previous' means one year prior or multiple, but the lookback_years parameter implies configurability. The coverage is sufficient for an AI agent to understand the tool's purpose and expected output.

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

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

Schema description coverage is 100%: both country_code and lookback_years have descriptions. The description adds minimal extra meaning beyond the schema, but it does clarify that lookback_years is the 'calendar-year window to request for every fixed indicator', which aligns with the schema's description. The description names the bundled indicators, giving context that country_code refers to the country for which these indicators are fetched. Baseline 3 is appropriate since schema covers parameter semantics adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it bundles six official World Development Indicators into a normalized country snapshot, specifying exact indicators (GDP, growth, population, inflation, unemployment, life-expectancy) and that it includes latest/previous observations plus source/license evidence. It distinguishes itself from generic data tools like data.clean or data.profile by focusing on World Bank development data retrieval.

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

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

The description implies usage for obtaining a comprehensive country-level economic snapshot with a single call, and mentions 'latest and previous' observations, implying time-series context. It does not explicitly name alternative tools or state when not to use it, but given the sibling list includes data.clean and data.profile for other data operations, the intended use case is clear enough. No exclusions or alternatives are stated, so it falls short of a 5.

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