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

Annotations declare readOnlyHint=true and openWorldHint=true, so the safety profile is already known. The description adds useful behavioral context beyond annotations by specifying the exact return values (Jaccard similarity, shared/unique tags, facet breakdown) and the domain-agnostic nature. It does not mention limitations or side effects, but given the annotations, this is appropriate. No contradiction with annotations.

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 four sentences, each serving a distinct purpose: function, outputs, use cases, and domain scope. It is information-dense without redundancy, no fluff, and logically ordered from core behavior to application context. This is exemplary conciseness.

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 moderate complexity (4 params, output schema present), the description is complete. It explains the core purpose, return values, use cases, and scope. The output schema covers return structure, so the description need not repeat it. No prerequisites or error conditions are mentioned, but none are critical given the tool's read-only nature and clear schema.

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 description coverage is 100%, so the schema already documents all parameters (entity_a, entity_b, entity_type, async) with examples. The description adds no parameter-specific information beyond what the schema provides, but it reinforces the conceptual meaning of entity_a/entity_b as content entities. This aligns with the baseline score of 3 when schema carries the semantic load.

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 function with a specific verb and resource: 'Compare the tag profiles of two content entities... and measure how similar they are.' It also lists concrete outputs (Jaccard score, shared tags, unique tags, facet breakdown), making the purpose unambiguous. While there is a sibling tool 'content_similar', the description effectively distinguishes this tool by framing it as a pairwise comparison, not single-entity similarity 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 explicitly provides 'When to use this tool' with concrete examples ('how similar are Dark Souls and Elden Ring?'), and lists use cases like positioning overlap and cross-sell opportunities. It also states it works across domains, giving strong contextual guidance. It does not explicitly name alternative tools, but the guidance is sufficiently clear for an agent to select this tool appropriately.

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