update_orders

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that 'data' is a JSON string of fields to update, suggesting a partial update, but it does not disclose what happens if the row_id does not exist, whether the update is atomic, or what the response contains. The tool is a mutation, yet the description lacks important behavioral details beyond the basic update action.

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 description is concise, consisting of two sentences that front-load the primary action and then clarify the data parameter. There is no unnecessary wording, making it efficient and easy to parse.

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?

Given the tool's simplicity (two required parameters, no enums, no nested objects) and the presence of an output schema, the description is largely complete. It covers the core update action and the meaning of the data parameter. However, it stops short of detailing edge cases or update semantics, such as whether the update is fully out-of-the-box safe, but the output schema likely handles return value documentation, so the description is adequate for typical usage.

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?

The input schema has no descriptions for its parameters (0% coverage), so the description must compensate. It adds meaning by explaining row_id as the identifier of the row to update ('by id') and data as a JSON string of fields to update. This is useful but still leaves gaps regarding the allowed structure of the JSON string and any constraints on field names, so it only partially compensates for the schema's lack of guidance.

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 clearly states the tool's purpose: 'Update a row in orders by id.' It identifies the resource (orders) and the action (update), distinguishing it from sibling tools like update_users and update_products. The additional mention that 'data = JSON string of fields to update' clarifies the scope of the update, making the purpose highly specific.

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 implies the tool is for modifying existing orders, as opposed to creating or deleting them, but it does not explicitly state when to use this tool versus alternatives like create_orders or delete_orders. There is no explicit 'use this when' or 'instead of' guidance, so the usage context is only implied rather than explicitly defined.

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