Entity presence: Google Knowledge Graph + Wikidata

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, which describe core behavior. The description adds context about a non-destructive side effect: providing steps to establish an entity if none exists. This is consistent with annotations and adds value beyond the metadata without contradiction.

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 concise with two sentences, clearly organized: first states the core function and data sources, then provides context about importance and a conditional behavior. It avoids fluff, though the mention of AI engines could be trimmed without loss, making it not perfectly efficient.

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?

The tool has 3 parameters, no output schema, and moderate annotations. The description covers the main purpose and one conditional result, but it does not explain the expected output format for the normal case or elaborate on the 'limit' and 'languages' parameters. For a relatively simple tool, this is adequate but has 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?

Only the 'name' parameter is described in the schema; 'limit' and 'languages' lack descriptions and are not mentioned in the tool description either. Schema description coverage is 33%, and the description does not compensate by explaining parameter usage, leaving most parameters under-specified.

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's purpose: 'Check whether a brand/business/place exists as an entity in Wikidata and in Google's Knowledge Graph Search API.' It also explains why this matters ('AI engines and Google rely on entities to know who a site is'), making the intent unambiguous. This distinguishes it from sibling tools like brand_mentions or reviews_snapshot.

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 provides implicit usage guidance by mentioning prerequisites (Wikidata free, Google requires API enablement and key) and a conditional result behavior ('if none exists, the result includes the steps to establish one'). However, it does not explicitly compare with alternatives or state when to use this tool over other knowledge-graph-related tools, leaving the context implied rather than direct.

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