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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds no extra behavioral detail such as how recommendations are derived, constraints, or side effects.

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?

One sentence, front-loaded with the key input ('Given a use-case/industry') and clear output ('AETumi assets and a production approach'). No wasted words.

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?

The description covers the core purpose and return concept but leaves the meaning/role of the optional 'framework' parameter unclear. Since there is no output schema, the description should clarify what the recommendation includes beyond 'architecture, performance'.

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 only 33%; use_case has examples, but industry and framework have no descriptions. The tool description mentions 'use-case/industry' but does not explain the optional framework parameter or how it affects recommendations.

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 action ('recommend'), the input trigger ('Given a use-case/industry'), and the output ('AETumi assets and a production approach'). This distinguishes it from search/list/pricing siblings.

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 implies when to use the tool ('Given a use-case/industry'), but does not explicitly mention when not to use it or contrast it with siblings like search_assets or get_asset.

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