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 of behavioral disclosure. It mentions the confirmation requirement, which is valuable context, but doesn't describe what 'Generate data table' actually does (e.g., creates a structured table in a notebook, potentially with data processing), what permissions are needed, whether it's reversible, or what happens on success/failure. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.

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 appropriately sized with a brief purpose statement followed by parameter explanations. However, it's not optimally front-loaded—the critical 'Requires confirm=True after user approval' is in the first sentence but buried after the purpose, and the Args section uses inconsistent formatting (e.g., mixing quotes and no quotes). Some sentences could be more efficient, like combining the confirmation requirement with the parameter explanation for 'confirm'.

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 5 parameters with 0% schema coverage and no annotations, but with an output schema present, the description provides basic coverage of parameters and a key behavioral constraint (confirmation). However, for a mutation tool that creates data tables, it lacks details on what the tool actually generates, error conditions, or how it interacts with the notebook system, making it minimally adequate but with clear gaps in context.

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%, so the description must compensate. It provides basic semantics for all 5 parameters in the Args section, explaining what each parameter represents (e.g., 'Notebook UUID', 'Description of the data table to create'). However, it doesn't add deeper meaning like format details for 'notebook_id' or what 'source_ids' actually refer to, leaving some ambiguity despite covering all parameters nominally.

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 verb 'Generate' and resource 'data table', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'notebook_add_text' or 'report_create' that might also generate content, leaving some ambiguity about when this specific table creation tool is appropriate versus alternatives.

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 provides implied usage guidance through the 'Requires confirm=True after user approval' statement, which suggests this tool should be used only after explicit user confirmation. However, it doesn't explicitly state when to use this tool versus alternatives like 'notebook_add_text' for adding content or 'report_create' for structured output, nor does it mention prerequisites beyond the confirmation requirement.

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