Debug Table Structure

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

Annotations already mark the tool as read-only, idempotent, and non-destructive; the description adds valuable behavioral detail by specifying exactly what the output contains and how to interpret fields like dimensions, position, current_content, and insertion_index. It also makes clear the tool inspects rather than mutates, with no contradiction to annotations.

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 long but well-structured with bolded trigger conditions, output explanations, and workflow steps that are easy to scan. Each section conveys actionable guidance, though some repetition of the tool's core purpose could be trimmed.

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 covers when to use the tool, how to read its output, and how it fits into a workflow, while the output schema handles the return structure. One minor gap: it references 'populate_existing_table' as a scenario, but that tool does not appear in the sibling tool list, creating slight routing ambiguity.

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 already documents all three parameters with helpful descriptions and a default for table_index. The description does not add parameter-specific guidance beyond what the schema provides, so the baseline score of 3 is appropriate given 100% schema coverage.

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 debugs table structure and enumerates what it reveals: dimensions, cell positions, current content, insertion indices, and boundaries. It is unambiguous about the resource and purpose, though it does not explicitly contrast with sibling inspection tools like inspect_doc_structure or create_table_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 an explicit 'USE THIS IMMEDIATELY WHEN' list and a workflow integration section covering after creation, before population, and after failures. It lacks an explicit when-not-to-use section or named alternative tools, so it stops 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.