Create Table with Data

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

The description discloses critical behavioral constraints: index must come from inspect_doc_structure, table_data must be a 2D list of strings with uniform rows, use empty strings not None, and verify with debug_table_structure. These go beyond annotations (readOnlyHint false, etc.) and add context for correct invocation.

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 lengthy but structured with sections and headers. It front-loads the purpose and then gives essential steps. However, there is redundancy in repeating the inspect_doc_structure requirement multiple times, so it is not maximally concise, but still efficient for a complex tool.

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?

For a 7-parameter tool with a mandatory prerequisite, the description covers the workflow, data format, and verification thoroughly. It does not need to explain return values as an output schema exists. This is essentially complete for a tool of this complexity.

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 covers all parameters with descriptions, but the description enriches table_data with an explicit example and explains the index requirement in detail. It also clarifies empty cell handling. This adds value beyond the schema, so a 4 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 opens with 'Creates a table and populates it with data in one reliable operation,' which clearly states the action (creates), resource (table), and scope (populates with data). This distinguishes it from sibling tools like append_table_rows or insert_doc_elements by focusing on table creation with data.

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 a mandatory workflow: always call inspect_doc_structure first, use total_length as index, format data as 2D list, then call this function. It also recommends debug_table_structure after creation. However, it does not explicitly state when not to use this tool versus alternatives, so it falls just short of a 5.

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