list_features

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and a closed world, so the safety profile is fully covered. The description adds only the sort order (tier then name) as genuine behavioral context; with annotations this strong, that is a modest addition.

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, front-loaded sentences with the action stated first and the return shape second. The field enumeration in the Returns block slightly overlaps the output schema, but the text is tight overall.

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?

With no parameters, full annotation coverage, and an output schema present, the description needs only to say what the tool does and what it returns — which it does, including ordering and the per-entry fields.

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?

The tool takes zero parameters, so the baseline is 4; the description correctly makes no parameter claims and instead describes the output fields, which is the only relevant semantic content.

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 resource — 'List every registered MCP-Dubai feature with its tool count and tier' — which is unambiguous. It does not, however, distinguish itself from adjacent discovery siblings such as recommend_tools, about, or list_plan_categories.

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?

Usage is implied by the listing nature of the tool (browse/discover available features), but there is no explicit when-to-use, when-not-to-use, or pointer to an alternative like recommend_tools for goal-driven discovery.

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