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

Annotations already declare readOnly/idempotent/non-destructive and closed-world, so the safety profile is covered. The description adds real behavioral context beyond that: results are ranked with owned tools first, and the response includes an honest case for keeping the tool.

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?

Three tight sentences with no waste, leading with what the tool produces and the ranking rule, then the precision tip, then the honest-case note.

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, no-output-schema tool, the description covers what is returned (per-capability alternatives, ranked, with a keep-case) and how to get better results. Minor gaps only, such as how team_size influences output.

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%, so the schema already documents all four parameters. The description only adds the origin of capabilities (from get_tool) and the $0-extra framing for owned_tools; team_size and the tool parameter get no extra meaning.

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 (list) and resource (capabilities + alternatives for a product), plus the distinctive output rule: owned tools ranked first at $0 extra. This differentiates it from siblings like compare_solutions and recommend_stack.

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?

Clearly frames the use case (a tool the user is considering dropping) and tells the agent to source capabilities from get_tool for precision. It does not explicitly name sibling tools to use instead, so it stops short of full routing guidance.

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