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

With no annotations, the description carries full transparency burden and excels. It discloses non-mutation ('without writing anything'), explains return fields (ok, error?, rewrittenFormula?, etc.), details what unknownFunctions and referencedFunctions mean, and warns about cells storing invalid formulas. It also notes cost and auth characteristics, all beyond any structured data.

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 front-loaded with the core purpose, then returns, then usage guidance, then internals. Every sentence adds value: the failure-mode example, the explanation of return fields, and cost/auth notes. No fluff or repetition despite covering multiple aspects.

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?

With no output schema, the description fully explains return values and their semantics. It also covers when to use the tool, side-effect-free behavior, environment requirements, and failure scenarios—complete for a single-parameter validation tool.

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 schema already covers the single parameter fully (example, max chars, leading '='). The description adds context about the parameter's role in validation but does not introduce new format or syntax details beyond the schema, so the baseline of 3 applies.

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 'Parse-check a formula expression server-side without writing anything', a specific verb and resource that clearly distinguishes it from evaluation tools. It also explicitly references update_row/create_row, making its role distinct from siblings like evaluate_formula.

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?

It provides explicit when-to-use guidance: 'Use BEFORE update_row / create_row when the formula references functions or syntax you're not 100% sure of'. It includes concrete examples of failures and clarifies prerequisites ('no auth, no workspace context needed'), leaving no ambiguity about appropriate invocation.

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