eval_formula

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

Even though annotations already declare readOnlyHint=true and destructiveHint=false, the description adds meaningful behavior: private scratch cell execution, no writes to user-visible cells, automatic leading '=' insertion, and the full return type contract including error and empty cases. This exceeds what annotations provide.

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 well-structured with a clear definition, a bulleted 'Use for' section, and a brief note about the leading '='. Every sentence adds useful information with no repetition or fluff.

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 documents the return value shape and all possible type values. It also covers safety, use cases, and syntax details, making it sufficiently complete for an agent to select and invoke the tool 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?

The single parameter expr is already well-documented in the schema with an example and the optional leading '=' note. The description adds further value by covering return types and BLOCKREF usage, but the schema already carries most of the parameter meaning, so this is strong but not a 5.

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 it evaluates an Excel-style formula in a private scratch cell and returns the computed value, which distinguishes it from mutation tools like set_cells or set_field_rule. The return format is also specified, making the tool's purpose unmistakable.

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 explicitly lists concrete use cases: quick checks, sanity-testing templates before set_field_rule, and BLOCKREF/BLOCKREFS lookups. It also clarifies that nothing is written to user-visible cells, implying it should not be used for write operations.

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