workiva_format_cells

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

With no annotations, the description carries full responsibility and delivers exceptionally: it discloses the 202 false-acceptance pitfall, names exactly which operations persist, recommends readback verification, and documents error cases (400 for DV/CF). It also clarifies the table_id token format vs UUID, preventing common misuse.

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?

Although lengthy, every sentence serves a purpose. It opens with the endpoint and key caveat, then systematically details persistence status, parameter formats, and JSON examples. Warnings and clarifications are clearly labeled (⚠️), and the structure helps the agent quickly extract critical behavioral facts without padding.

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 complexity of the endpoint and the lack of annotations, the description covers all necessary context: parameter semantics, persistence expectations, alternatives for unsupported formatting, error behavior, and verification advice. The existence of an output schema further reduces the need to describe return values, so completeness is high.

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 0%, so the description must explain both parameters. It does so thoroughly: table_id is described as an opaque content-table token (not a 32-hex UUID), and operations includes concrete JSON examples for setCellsProperties and setCellsBorders, plus a note about formatCells. This exceeds what the bare schema (just names) provides.

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 formats cells via a specific endpoint, and contextually distinguishes itself from siblings like workiva_write_cells (cell values) and workiva_read_cells (cell reading). It also specifies the scope (cell properties, borders, formats) and notes when to use a different path for font/bold/size, making its purpose unambiguous.

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 explicit when-to-use guidance, including which operations actually persist (setCellsProperties, setCellsBorders) and which don't (formatCells on v2026), with a clear recommendation to use api_request for font/bold/size. It also lists unsupported operations (valueFormat, dataValidation, conditionalFormat) and their error behavior, effectively telling the agent when to avoid this tool.

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