get_entity

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

No annotations are provided, so the description carries the full burden. It discloses that the tool fetches 'complete details' including properties, memberships, and relationships, and specifies that 'Relationships come from the OpenSanctions knowledge graph' with examples like 'ownershipOwner'. However, it lacks details on potential errors (e.g., invalid ID), rate limits, or authentication needs, which are relevant for a read operation.

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 front-loaded with the core purpose in the first sentence, followed by usage guidelines and additional details. Each sentence adds necessary information without redundancy, making it efficient and well-structured for quick comprehension.

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's complexity (fetching detailed entity data), no annotations, and no output schema, the description does well by covering purpose, usage, and data scope. However, it could improve by mentioning the response format or potential limitations (e.g., data freshness, error cases), leaving minor gaps in completeness.

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?

The input schema has 100% description coverage for the single parameter 'entityId', so the baseline is 3. The description adds value by specifying the parameter's purpose ('to get the full picture') and providing an example format ('e.g., NK-...'), which enhances understanding beyond the schema's basic type and requirement.

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 action ('Fetch complete details') and resource ('specific entity by ID'), specifying the scope includes 'all properties, dataset memberships, and relationships to other entities'. It distinguishes from siblings like 'search_entities' (which finds entities) and 'match_entity' (which matches entities), making it specific and non-tautological.

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 explicitly states when to use this tool: 'Use this after finding an entity via search or match to get the full picture'. This provides clear context for usage relative to alternatives like 'search_entities' and 'match_entity', with no misleading or missing guidance.

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