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

Annotations already declare readOnlyHint=true and openWorldHint=true, which the description agrees with (an audit is read-only; openWorldHint fits the free/no-LLM-calls claim). Beyond annotations, the description adds valuable behavioral traits: 'Free (no LLM calls)' signals cost/performance characteristics, and the scope disclosure (25 crawlers, /llms.txt, hygiene checks) sets accurate expectations for what the audit covers. No contradiction exists.

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 purpose is front-loaded in the first clause, and the structure flows logically: purpose → consequence framework → scope enumeration → cost signal. Every sentence earns its place. It runs slightly long due to the parenthetical crawler name lists and the em-dash framing, but both carry genuine decision-making value for the agent. Minor trimming possible without losing substance.

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 single-parameter tool with readOnly/openWorld annotations, this is nearly complete: it explains scope, the decision framework, and cost profile. The only gap is the absence of any description of the output/return format — and since there is no output schema, the description carries that burden entirely. This is a minor omission against an otherwise thorough definition.

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 description coverage is 100% — the single 'domain' parameter is fully documented in the schema ('Root domain to audit, e.g. 'yoursite.com''). The description references the site implicitly but adds no parameter-level detail beyond the schema. Baseline 3 is appropriate since the schema already carries the full burden.

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 a specific verb+resource: 'Audit which AI crawlers a site allows or blocks in robots.txt.' It further distinguishes itself by enumerating its exact scope (25 known AI crawlers, /llms.txt existence, robots.txt hygiene), which clearly separates it from the sibling ai_visibility_report and other SEO tools in the list. The purpose is unambiguous and non-tautological.

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 strong implied context — it frames the audit around the visibility-vs-training crawler decision, making it clear this is a pre-decision check before blocking or allowing crawlers. However, it never explicitly states when to choose this tool over siblings like ai_visibility_report or site_audit, nor does it name alternatives or exclusions. Usage is inferable but not stated.

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