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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and scope are covered. The description adds the useful fact that each entry carries an answer count, but says nothing about ordering, result volume, or whether it is scoped to the calling agent.

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 short clause with no filler, and the resource is front-loaded. The phrasing is a bare noun phrase rather than a sentence, which is terse but slightly less crisp than an explicit verb.

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-parameter list with no output schema, the description covers the resource and one return attribute, which is close to adequate. It still omits whether results are paginated or bounded, and whether the list is global or limited to questions the caller asked.

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 there is nothing for the description to disambiguate and the baseline is 4. No parameter-related gaps exist.

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 names a specific resource (questions asked to humans by AIs and by humancollab) and adds what the listing carries (answer counts), so an agent knows exactly what it retrieves. It does not, however, distinguish this list from the related get_answers or ask_question 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?

There is no statement of when to call this versus get_answers (fetch responses) or ask_question (create one). The 'list_' prefix implies enumeration, but the choice among the three question-related siblings is left entirely to inference.

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