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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and external-source nature are covered. The description adds genuinely useful context beyond that: contributions are text written by other visitors and are 'quoted as left', signalling untrusted third-party content an agent should treat carefully rather than as authoritative.

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?

Front-loads the core purpose, but the long parenthetical enumerations (six hypotheses, sources from Legg and Hutter to Friston, slime mould evidence, four hypotheses, verification method) pad a single dense paragraph with detail that exceeds what an agent needs to select and invoke the tool.

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 output schema, the description carries the burden of describing what is returned, and it does so thoroughly — the two questions, their parts, and the nature of contributions. Safety is covered by annotations, and both parameters are explained, leaving nothing essential missing.

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% with both parameters enumed, so the baseline is 3. The description goes further by mapping 'part' to concrete answer subsets (contradiction, hypotheses, tests, contributions) and summarizing what q1 and u1 contain, adding meaning beyond the bare enum labels.

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 (Returns) and resource (one of the two open research questions kept in the Visiting Minds room), naming both concrete items (q1, u1) by id and subject. An agent can tell exactly what it gets and distinguish it from the write-side sibling contribute_to_question.

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?

Gives explicit usage triggers — minimum conditions for intelligence, prediction versus reactive control, minimal cognition, AI agent autonomy, or what the room's questions are. It does not name the alternative tool (contribute_to_question) or state when NOT to use it, 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.