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

Annotations already mark the tool as read-only and non-destructive, and the description adds meaningful behavioral context: 'Record links are capped; records_truncated signals omitted links,' 'neighbors_limit=0 skips neighbors,' and 'No LLM call.' These details go well beyond what annotations alone provide and set accurate expectations about output limits and deterministic behavior.

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 dense but every sentence adds value: capabilities, output truncation, parameter edge case, downstream use, determinism, cross-space warning, and a docs pointer. Front-loading the main function makes it immediately scannable for an agent.

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 small parameter count, strong annotations, and presence of an output schema, this description is complete. It covers what is returned, how results are limited, how neighbors can be skipped, how to use the results, and important constraints. An agent can invoke this tool correctly without needing additional clarification.

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 50%, with concept_id documented but neighbors_limit lacking a description. The description compensates by explicitly explaining 'neighbors_limit=0 skips neighbors' and clarifies nearest-neighbor behavior with 'within its own type/model slice.' It does not add much for concept_id, but the schema already covers that parameter adequately.

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 opens with a specific verb and resource: 'Read one concept's aliases, identity source keys, linked records and nearest neighbors.' It also adds scope by saying 'within its own type/model slice,' which differentiates this tool from broader semantic list/merge operations. This is clearly more informative than the tool's title alone.

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?

It gives a concrete workflow: 'Use returned alias IDs with update_concept_alias and similarities to assess a proposed merge.' It also warns against comparing similarities across embedding spaces or concept types. It does not explicitly name sibling alternatives or when-not-to-use conditions, but the context is clear enough to guide correct selection.

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