append_table_rows

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

Annotations include destructiveHint=true, so the agent already knows the operation is destructive. The description adds a small behavioral detail (rows are matched by headers), but it does not disclose potential side effects such as structure changes or failures when headers don't match. It neither contradicts the annotations nor significantly enriches them.

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, clear sentence with no redundancy. It efficiently conveys the core action and key constraint. Every word 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?

Given the tool's complexity (8 parameters, destructive annotation, no output schema, and many sibling tools), the description is far too sparse. It doesn't explain the append process, how headers are matched, error conditions, side effects, or when to choose this over similar tools. The lack of parameter descriptions and behavioral context makes it incomplete for an AI agent to use it correctly.

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 does explain the 'rows' parameter by specifying 'dictionary-shaped rows' and 'matching worksheet headers', which clarifies the expected format. However, it provides no meaning for other parameters like dry_run, header_row, include_changes, allow_structure_change, or expected_structure_token, leaving most of the parameter space unexplained.

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 action (append), the object (dictionary-shaped rows), and the mechanism (matching worksheet headers). It is specific enough to convey the core function. However, it does not explicitly distinguish itself from the similar sibling tool 'append_excel_table_rows', so it loses a point for sibling differentiation.

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 no guidance on when to use this tool versus alternatives like 'append_excel_table_rows', 'upsert_excel_table_rows', or 'insert_rows'. The phrase 'by matching worksheet headers' hints at a precondition (rows must be dictionaries with keys matching headers) but does not clarify context or exclusions. This is effectively no guidance.

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