get_data

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

With no annotations, the description must disclose behavioral traits. 'Auto-correction' is mentioned but not explained, and there is no detail about return format, limitations, or side effects. This is a significant gap for a data-fetching tool.

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, front-loaded with the main action. It is concise and free of fluff, though the unexplained 'auto-correction' term introduces ambiguity.

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?

Despite the presence of an output schema, the description lacks essential context: what 'auto-correction' does, how years and economies interact, and what the returned data structure represents. This is incomplete for a tool with moderate parameter complexity and important behavioral nuances.

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 0%, so the description must compensate. It explains 'labels=True' yields human-readable country names, but years, economies, and indicator_code are left purely to their types. This is only partial value addition.

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 the tool fetches World Bank data, using a specific verb 'fetch' and resource. It distinguishes from siblings like search_indicators and plot_chart, though the phrase 'auto-correction' is vague. Overall, the core purpose is clear.

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?

No guidance is provided on when to use this tool versus alternatives like compare_countries or analyze_trend. The usage context is only implied by the sibling names, not explicitly stated.

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