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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower; the description still adds real substance by saying the plan derives from the latest check, that moves are ranked by how many questions and AIs each can win, and that it includes rival and source-page context. It does not discuss freshness/latency or what happens when no check exists yet.

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 what the plan is, then the usage example and the follow-on tools; every sentence carries information. The opening sentence is dense with nested clauses, which costs a little readability but not waste.

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?

Output schema exists so return shape needn't be explained, the sole parameter is fully documented, and annotations cover the safety profile. The description fills its remaining job: what the plan contains and how to act on it.

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?

Single parameter with 100% schema description coverage that already explains domain/id/name forms and the omit-when-one-site case. The description adds no syntax or default semantics beyond the schema, 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 concrete resource and verb: 'One site's plan from its latest check', then enumerates what the plan contains (per-AI naming reasons, ranked moves, rivals beaten, pages read instead). It is clearly distinct from siblings like questions or rivals, though it does not explicitly contrast with the close neighbor 'briefing'.

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 an explicit trigger phrase ('what should I improve first on biotree.bio?') and routes the agent onward: use build_prompt to hand a move to a coding session, mark_move_done once shipped. When-to-use and next steps are both named, leaving little to inference.

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