lookup_knowledge_graph_entities

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It explains the MID format and that the tool looks up entities, which implies a read-only operation, but it does not mention what is returned, language handling, or any limitations. This is adequate but not rich.

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?

Two short sentences: the first states exact purpose, the second provides usage context and MID examples. Every word earns its place; no fluff.

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?

With only two parameters and no output schema, the description is reasonably complete for usage. However, it does not explain what the lookup returns (e.g., entity details, names, descriptions) or mention the languages parameter, leaving some ambiguity for the agent.

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 descriptions for both `ids` and `languages`. The description adds a second MID format example (/g/11b6vwtjpg) beyond the schema's single example, providing a slight enhancement, but it does not discuss the `languages` parameter. Baseline 3 is appropriate.

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 'Look up specific Knowledge Graph entities by their Machine IDs (MIDs)', which is a specific verb+resource+scope. It also distinguishes from the sibling tool by explicitly mentioning use after a previous search.

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 says 'Use this when you already know the entity IDs from a previous search', which gives clear context for when to use it. It implies search_knowledge_graph is for when you don't know IDs, but doesn't explicitly name the alternative or state when not to use it.

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