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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds useful scoping context in stating these dimensions are configured per-tenant and 'injected into the bound analytics view for this tenant only.' Beyond that it says nothing about result size, ordering, or how the view/entity_type filters alter 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?

Two short paragraphs that lead with the core action, then the reason to call it. Every sentence carries weight, with no redundancy against the annotations. Minor cost for the dense 'virtual Business Context entity types' phrasing, but overall 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?

For a read-only, zero-required-parameter list tool with full schema coverage and no output schema, the definition supplies what an agent needs to decide to call it and why. The one gap is a hint about what a returned dimension record contains, which would help an agent use the results. Given the annotations and complete schema, that omission is minor.

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%, with clear descriptions and examples for view, entity_type, and include_empty, so the schema already carries parameter meaning. The description never references any of the three parameters, and in particular does not clarify how include_empty changes the result or what filtering by 'view' does conceptually. Baseline 3 is appropriate when the schema does all the work.

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: 'List tenant custom report properties configured on virtual Business Context entity types.' That clearly separates it from mutating siblings such as report_custom_dimension_upsert and report_custom_dimension_delete. The 'virtual Business Context entity types' phrasing is jargon-heavy, which mildly blurs what exactly is returned, but the core intent is unambiguous.

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 an explicit usage condition: 'Use this before adding a new report property so existing dimensions, such as customer segment, are preserved.' That is actionable when-to-use guidance tied to a concrete workflow. It stops short of explicitly naming the upsert tool as the alternative or stating when not to call this (e.g., if you only need the query result), which keeps it from being a 5.

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