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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds that the responder is a named expert persona and that answers may include product/coaching/pricing information, which is useful context. It does not say whether responses are advisory only, whether the 'expert' is an AI persona, or what form the answer takes.

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?

One sentence, front-loaded with the primary use case and efficiently listing topics. The appended product/pricing clause is slightly awkward in a single breath but adds real scope rather than 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?

With no output schema, the description should convey what the agent gets back; it says only that Figs answers and that product/coaching/pricing info is available. For a simple one-parameter conversational tool this is close to adequate, but the absence of any statement about answer style, scope limits, or intent routing leaves a meaningful gap.

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 0% for the single required 'question' parameter, so the description must compensate. It partially does by enumerating acceptable topics and hinting that both relationship questions and product/pricing questions are valid inputs. However, it gives no guidance on phrasing, length, or whether one question per call is expected.

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 states a specific verb ('Ask') and resource ('relationship expert Figs O'Sullivan') and enumerates topical domains: love, conflict, trust, attachment, intimacy, repair. It also declares a secondary purpose (learning about Figlet AI, coaching modes and pricing). It does not name or contrast any sibling such as repair_right_now or get_relationship_assessment, so differentiation is left to inference.

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 topic list implies when to use it (general relationship questions spanning love, conflict, trust, attachment, intimacy, repair), but there is no explicit when-not guidance, no prerequisites, and no mention of alternatives like repair_right_now or name_conflict_pattern. The dual purpose of product/pricing inquiry is stated without saying how to signal which intent is wanted.

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