Goal Seek

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

Annotations already flag a destructive mutation, and the description adds important behavioral details: 0.001 tolerance, at most 100 iterations, and no changes if convergence fails. This is exactly the extra context an agent needs beyond the safety hints.

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?

Two sentences, front-loaded with the operation and followed by convergence and failure behavior. There is no filler.

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?

For a five-parameter mutation tool with no output schema, the description supplies the main unknowns: convergence criteria and failure semantics. The remaining `path` and `sheet` details are low-risk schema-level concerns.

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 60%, and the description clarifies the three key semantic parameters: the formula cell, target value, and constant to change. It does not explain `path` or `sheet`, leaving those to schema names alone.

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?

States a specific operation—goal seek—with exact roles for `cell`, `target`, and `changing_cell`. It clearly distinguishes itself from siblings like `write_range` because it iteratively solves for a target rather than writing a supplied value.

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 implies the usage scenario—solve for a target by adjusting a constant—but does not explicitly say when to choose it over direct writes, formula tracing, or other sibling tools. No alternatives or exclusions are named.

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