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

Annotations already declare readOnlyHint=true, so the description carries a lower burden for safety disclosure. The description adds valuable behavioral detail by enumerating exactly what data is returned (list price, group price, buyer counts, committed counts, want counts, spots left, deadline) and how the optional parameters affect the response. This transparency goes beyond the annotation's binary read-only flag.

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 two sentences, front-loaded with the core output list, then explains parameter usage. Every phrase earns its place, with no redundancy or filler. The structure is efficient and easy to scan.

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 read-only status tool with no output schema, the description covers the essential return data and parameter semantics. It does not detail error cases or pagination, but given the tool's simplicity and the annotations covering safety, it is sufficiently complete for an agent to call it correctly. The only minor gap is lack of explicit guidance on when to choose this over a sibling tool.

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 described. The description reinforces and extends the schema by clarifying that 'chain' defaults to the live product when omitted and that 'email' reveals a specific person's spot. This adds contextual meaning beyond the schema's simple descriptions, such as the default behavior for the chain parameter.

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 clearly states the tool's function: it reports live status of a product chain, including price, counts, spots left, and deadline. It also explains how to query a specific product via slug, distinguishing it from a generic list tool. The verb 'what's live' plus the resource and specific data fields make the purpose unambiguous.

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 implies usage: it defaults to the live product unless a slug is given, and an email shows a person's spot. However, it does not explicitly mention when to use this tool over alternatives like get_chain or list_chains, nor does it state any exclusions or prerequisites. The guidance is adequate but not explicit about tool selection.

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