contact_seller

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

Beyond the sparse annotation (destructiveHint=true), the description adds meaningful operating facts: messaging is free, no prior purchase is needed, and sellers typically respond within 24 hours. One gap: it never addresses why a mere message would carry destructiveHint=true or what side effects (e.g., creating a conversation thread) occur.

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?

Three tightly written sentences, front-loaded with the action and followed by the two most decision-relevant facts (cost/prerequisites and expected latency). No sentence is 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 covers what an agent needs to decide and call: purpose, cost, prerequisite waiver, question scope, and turnaround time. It is slightly thin on the outcome of a successful send and does not reconcile the destructiveHint annotation.

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%, so all four parameters (including the optional dataset_id) are already documented in the schema. The description's mention of freshness/schema/coverage/update-frequency only loosely maps to message content and adds no syntax or format detail beyond the schema, so the baseline of 3 applies.

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 opens with a specific verb + resource ('Send a message to a dataset seller') and enumerates the concrete question types it supports. It is unmistakably distinct from siblings like get_dataset, buy_now, or query_dataset, so an agent can route to it without inspecting the 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?

It states the operative context clearly: use this to ask questions before purchasing, and note that no prior purchase is required. However, it never names an alternative tool or an explicit when-not-to-use condition, so usage is well-contextualized but not fully disambiguated.

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