get_entity_data

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

Annotations already declare readOnly, non-destructive, idempotent, and closed world. The description adds behavioral details: returns JSON rows with a concrete example, explains automatic join via shadow columns, and specifies a max of 10 indicators. No contradictions.

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?

Three sentences, front-loaded: first sentence states action and scope, second explains unique join capability, third shows return format and use cases. No wasted words, every sentence earns its place.

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 no output schema, the description provides a return format example and covers entity, indicators, time, join mechanism, and use case. It does not address error cases or limits on time ranges, but for a read-only data fetch tool with good annotations, it is sufficiently complete.

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 coverage is 100% with basic descriptions. The description adds valuable context: indicators come from list_indicators/get_entity_profile, max 10 allowed, time parameter is optional and can be a range. This goes beyond the schema alone.

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?

Description clearly states it fetches wide-format data for one entity across multiple indicators with automatic time join. It highlights the cross-dataset join capability, distinguishing it from sibling tools like compare_entities (multiple entities) and get_entity_profile (single indicator).

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?

Explicitly says 'Perfect for multi-indicator dashboards or correlation analyses', giving clear use cases. Does not mention when to avoid it or list alternatives, but the description implicitly excludes multi-entity use and automatic join sets it apart from manual query tools.

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