suggest_listing

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

Annotations only give destructiveHint=true, whereas the description discloses the draft/approval workflow, the returned approval URL, and the contents of message_for_user (approval link and suggested price) — meaningful behavior beyond the annotation. It stops short of covering permissions, failure modes, or the draft's lifecycle.

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 packed sentences, front-loaded with the action and immediately followed by the outcome and the returned artifact. No filler or repetition of schema content.

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 usefully explains the return surface (approval URL, message_for_user with link and price), which is exactly what an agent needs after a mutation. It omits failure/error behavior and what the created draft's status looks like, leaving a small 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 description coverage is 100%, so the schema already carries all five input parameters with examples and the category enum values. The description adds no syntax or format detail for the inputs, so the baseline 3 applies; its message_for_user note describes an output field, not an input.

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 (propose) and resource (dataset for listing on DataBazaar) and scopes it to research byproducts. The draft-pending-approval outcome distinguishes it behaviorally from sibling tools like create_listing and publish_listing, so an agent can tell what this does without opening 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?

The 'e.g. produced as a research byproduct' framing implies when to reach for it, but there is no explicit when/when-not guidance and no sibling (create_listing, publish_listing) is named as an alternative. Usage is inferable but not stated.

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