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

Annotations only declare this is a non-readonly write. The description adds real behavior beyond them: a human-in-the-loop confirmation step before sending, a content-integrity constraint ('Don't invent details they didn't give'), and post-send behavior (the team reads every submission and can reply by email). It stops short of stating auth or rate-limit behavior.

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-loaded with the purpose in the first clause, then organization guidance, then the confirmation and response notes. Dense but each sentence carries actionable content; no filler.

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 write tool with no output schema, the description covers the essentials: what to send, how to structure it, the confirmation gate, and what happens afterward (team reads, replies by email). Only the absence of auth/error context keeps it from being fully 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 100% with per-field examples, so the baseline is 3. The description goes further by mapping intent to fields — short title, details, where it applies, why it matters, and for a bug the repro steps plus actual vs expected — giving the agent guidance on how to populate them.

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 — send feedback to the ShearQuery team — and enumerates the three kinds (bug, improvement, feature), so the agent knows exactly what this does. It does not, however, distinguish itself from the sibling contact_shearquery_support, so it falls short of a 5.

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 usage context ('whenever the member or agency wants to, including while working through an idea with you') and a procedural precondition (show them the report and get their OK before sending). It does not name when NOT to use it or point to contact_shearquery_support as an alternative, so no exclusions.

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