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

Description states 'nothing is written and no model is called', fully disclosing side-effect-free and compute-light behavior. Consistent with readOnly and idempotent annotations.

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?

Well-structured and not overly long, but some redundancy exists between the axis list and the later examples. Minor trimming could tighten it without losing clarity.

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?

Even without an output schema, the description fully specifies the output shape (one line per axis, pass/fail/unavailable), enumerates the axes, and explains the verbose flag. Enough for an agent to know what to expect.

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 boolean parameter is covered by the schema, and the description adds concrete meaning: including the full table and axis definitions in the output. Slight room for explaining the default false behavior, but schema already covers type/default.

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?

Clearly states the tool runs an audit and returns pass/fail/unavailable lines per verification axis. The list of axes and the specific use cases make the 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?

Explicitly tells when to use it: before starting a run or when a tool answer looks wrong. Also clarifies it is free and unmetered, removing cost concerns.

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