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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so 'Read-only' and 'Idempotent' are largely redundant. The description does add genuine behavioral facts beyond the annotations: promoted/dropped ideas are filtered out of results, and the read does not advance the unread cursor.

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?

Four short sentences, front-loaded with what the tool returns, followed by filtering, differentiation from the sibling, and side-effect notes. Nothing is padded and every sentence adds information.

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 read tool with no output schema and full annotation coverage, the description supplies the returned record shape, the filtering rule, the sibling differentiation, and the unread-cursor side effect. An agent has everything needed to call it correctly.

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?

Zero parameters, so the schema carries no semantics and the baseline is 4. The description compensates usefully by enumerating the fields each returned idea contains, which is the only place that shape is documented since there is no output schema.

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 and resource ('List currently parked ideas in this Space') plus the returned fields (id, body, raised_by, status). It explicitly distinguishes itself from the sibling board/list_board tool by saying the board only reports parking_count while this returns the lot itself.

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 a clear selection rule against the closest sibling ('Board list only reports parking_count; this is the lot itself'), so an agent knows to call this when it needs the actual parked ideas rather than a count. It doesn't spell out exclusions relative to park_idea/promote_idea/drop_idea, but the list-vs-mutate distinction is obvious from the verb.

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