data_table_create

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

With no annotations provided, the description carries the full burden. It discloses that the tool 'Saves the table', which is important persistence behavior, and notes that filling is optional. However, it does not mention what happens if the table already exists, whether it overwrites or fails, or any permissions required. This is a partial disclosure.

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 a single, concise sentence that front-loads the core action and includes important details (optional rows, saving) without unnecessary verbosity. Every phrase earns its place.

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?

The description adequately covers creation, optional filling, and saving. However, with no output schema and no annotations, it leaves out details like return value, error behavior, or relationship to sibling tools. For a tool with 4 parameters, this is acceptable but not fully complete.

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 most parameter meaning is already structured. The description adds an example JSON format for rows_json, which is helpful, but does not significantly enhance understanding beyond the schema properties. Baseline of 3 is appropriate.

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 primary action: 'Create a DataTable for a row struct'. It also mentions optional filling from JSON and saving, which specifies the resource and outcome. This distinguishes it from sibling tool 'data_table_fill_from_json' by emphasizing creation rather than just filling.

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 usage: use when you need to create a new DataTable, optionally filling it with rows. However, it does not explicitly mention when to use an alternative (e.g., data_table_fill_from_json) or provide exclusions. The phrase 'optionally filling' hints that filling is not the primary purpose, but explicit guidance is missing.

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