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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses that this is a one-way mailbox, stored for human review, never publicly rendered, never auto-ingested, maintains C1 source-verification, and enforces a 10-submissions/day per-agent cap. This is rich behavioral context well beyond a bare mutation hint.

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?

The description is compact, front-loaded with the purpose, and uses a structured list for the three feedback types. Every sentence adds value: conditional requirements, behavioral guarantees, and the rate limit. No filler or redundancy.

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 submission tool with an output schema present, the description covers all essential aspects: purpose, three usage modes, required fields per mode, behavioral guarantees, and rate limiting. Though the 'agent' parameter is not described, the combination of schema defaults and the description's conditional logic makes the tool adequately complete.

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 0%, so the description must compensate, and it largely does. It explains the meaning and valid values of 'type', and the conditional requirements for 'topic_id' and 'source_url'. The 'agent' parameter is left undocumented, and 'message' is implied by context, but all critical conditional logic is conveyed.

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 opens with a clear verb+resource statement: 'Leave feedback for the station's human maintainers.' It then distinguishes three concrete feedback types (data_request, error_report, knowledge_lead), which fully clarifies the tool's scope and differentiates it from the sibling retrieval/search tools.

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 description provides explicit guidance on when to use each feedback type, including conditional requirements like topic_id for error_report and source_url for knowledge_lead. It does not explicitly state when not to use the tool, but the sibling tools are clearly unrelated, and the one-way/cap semantics imply this is reserved for human-maintainer feedback rather than general queries.

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