suggest_resources

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds the 'cloudHPC scalability rules' context but does not disclose output behavior, such as what the suggestion response contains or whether external data is queried.

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 front-loaded with a clear one-sentence purpose, followed by a compact parameter legend. Each line adds useful information, though the fds_* entry is terse to the point of ambiguity.

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 9 parameters, no output schema, and minimal annotations, the description covers most parameter semantics but is incomplete in important areas. It does not describe the return value shape, and the fds_meshes, fds_mpi_groups, and fds_total_cells parameters are not fully specified. The case_folder note also conflicts slightly with solver being a required schema parameter.

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 0%, so the description carries the full semantic burden. It does this well by explaining the domain-specific meaning of cells, nodes, elements, fds_*, case_folder, and prefer_speed, with solver examples. However, the fds_* parameters are grouped vaguely and not individually disambiguated.

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: 'Suggest vCPU and RAM type for a run'. This clearly differentiates the tool from siblings like list_machine_options or launch_simulation, since it is about recommendation rather than listing or launching.

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 intended use case, suggesting resources for a cloudHPC run, is implied by the first sentence and the parameter notes. However, there is no explicit discussion of when to prefer this tool over siblings such as list_machine_options, nor any stated exclusions or alternatives.

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