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

No annotations exist, so the description carries the full burden and does so: it discloses auth requirements (401 for missing login, code=40003 with data.bindUrl for unbound cloud-marketplace instances), the input_required dynamic consent flow, duplicate-booking behavior (returns the original serviceid and existing payUrl), the 30-minute payUrl expiry, and the contactSaved=false partial-success case. The privacy warning about ID numbers appearing in the conversation and the instruction not to echo them back is exactly the kind of behavioral context structured fields cannot convey.

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 content is dense but delivered as one unbroken block with no headings, ordering, or line breaks, making the branching logic hard to scan. Some material is out of scope for a booking call, such as the post-booking H5 capabilities (pay, reschedule/cancel, view reports), which inflates length without helping the invocation.

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 20-parameter mutation tool with no annotations and no output schema, the description is remarkably complete: it names the return fields (contactId, serviceid, orderEntryUrl, payUrl, contactid, contactSaved), the status-vs-rsvStatus distinction, and every elicitation fallback path. The main gap is the unexplained required identifiers hospitalCode, vendorid, and appointmentDate, which an agent must guess at.

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% across 20 parameters, so the description must compensate and it does for the tricky ones: planId, contactId, contactDraftId, consent, consentText, IDType (SFZ validation rules), and the birthday/gender required-only-when-not-ID-card rule. However, hospitalCode, vendorid, appointmentDate, payType, timespan, customerID, customerName, and customerMobile receive no explanation at all, leaving a substantial share of parameters ambiguous.

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 opening states a specific verb and resource ('体检预约：按 planId 取出项目，交给伙伴接口下单'), so an agent knows this creates a booking from a plan. It is implicitly distinguished from reservation_cancel and reservation_modify, but those siblings are never named or contrasted, so the differentiation is inferred rather than stated.

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 lays out explicit branching: use contactId directly when present; otherwise show the elicitation form picker, and fall back to contactMethodRequired/contactRequired for non-form clients. It also routes the agent to contact_list after the H5 flow. It stops short of explicitly saying when to choose this over reservation_modify/cancel, but the conditional guidance is unusually thorough.

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