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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantial context beyond them: the evidence is restricted to rated evidence, and the return payload is itemised (cases by kind of work, themes with practice counts for company size, claim checks, figure groups). It stops short of covering behaviour when no inputs are supplied or any result limits, so not a 5.

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?

Front-loaded with purpose and output composition, with no filler sentences. It is a dense, comma-chained construction whose middle clause ('open the cases... fetch eight to twelve records') mixes usage procedure into the purpose statement, costing a little scannability.

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?

There is no output schema, and the description compensates by enumerating exactly what comes back and how to act on it (fetch eight to twelve records and write from them). Combined with the when-to-use guidance, an agent has everything needed to select and invoke it.

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% and the schema itself carries the enum mapping instructions and size-band definitions. The description only adds that the company's size drives practice counts in the returned themes, which is mild extra meaning rather than documentation of the parameters themselves. Baseline 3 applies.

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?

States a specific verb and artifact ('Prepare a one-page board brief') plus the subject matter ('a question about AI adoption') and the constraint ('from rated evidence only'). It is clearly distinguishable from review_ai_transformation_plan, which it names.

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?

Explicit trigger ('Use it when someone needs a summary for a board, an owner or an investment committee') and an explicit exclusion with the correct alternative ('To review a written plan, use review_ai_transformation_plan'). Nothing is left to inference.

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