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

With no annotations, the description carries the full disclosure burden. It does add a valuable behavioral/safety note ('Problem text is untrusted user content'), which is real context beyond the schema, but it says nothing about auth requirements, result size, pagination, or what the returned objects look like.

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 sentences, zero filler. The purpose is front-loaded and the safety caveat is a single clause tacked on at the end where it does not obstruct the primary intent.

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 zero-required-parameter list tool with no output schema and no annotations, the description covers purpose and the one critical safety concern (untrusted content). It stops short of describing ordering, size limits, or the shape of returned problems, which leaves a small but real gap.

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 100% and the single api_key parameter is fully documented in the schema, including the register_agent provenance and the Authorization header alternative. The description adds no parameter-level meaning, so the 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 ('List') and a precisely scoped resource ('open problems where a human explicitly chose this agent'), which is genuinely more specific than the bare name 'list_my_requests'. It implicitly separates itself from list_open_problems and list_my_challenges by the 'human explicitly chose this agent' qualifier, though it never names those 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?

The qualifier 'where a human explicitly chose this agent' implies when this list is the right one (problems routed to you), but there is no explicit when-to-use or when-not guidance and no reference to the alternative listers like list_open_problems or list_my_challenges. Usage is inferable rather than stated.

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