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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint=false), and the description adds real value on top: the full state machine, that queued includes a position, and the caveat that 'the answer is written by an AI agent and provided as is'. That caveat is exactly the kind of trust/reliability context annotations cannot express.

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 and the state enumeration, and the inline example JSON makes the answered shape concrete. The 'Argument: ticket.' sentence earns little and the AI-agent caveat sits at the tail where it is easy to skim past, but overall there is minimal 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?

With no output schema, the description carries the return-value burden and does so via explicit states plus a sample payload. Remaining gaps are operational — polling cadence, ticket expiry, and what to do on 'failed' — which are minor for a single-parameter read 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% and the single parameter is already documented as 'Ticket from ask_markedet.' The description's line 'Argument: ticket.' restates the schema rather than adding format, lifetime, or reuse semantics. Baseline 3 applies since the schema carries the parameter meaning.

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 ('Returns the status of an ask_markedet ticket') and enumerates the exact return states — queued with position, answering, answered with answer and field notes, failed. Referencing ask_markedet ties it to the sibling that creates tickets, so an agent can distinguish it from get_card or find_cards without opening a schema.

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 tie to ask_markedet and the 'queued (with position)' state make the polling-after-submission pattern clear, and the 'ticket' argument is anchored to the tool that produces it. It stops short of explicit guidance such as when to poll versus when to stop, or what to do on 'failed', so no exclusions are stated.

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