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

Goes well beyond readOnlyHint/openWorldHint/idempotentHint by disclosing how the check is performed (robots.txt, Content-signal/Content-Usage, RSL licences, a live honestly-identified request) and the operating stance: no CAPTCHA solving, no proxies, no spoofed user-agents. It also states that refusals surface as findings with evidence rather than errors, which is exactly the behavioral context an agent needs.

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?

Front-loads the one-line purpose, then mechanism, then the full verdict space, then the non-evasion guarantee. The long parenthetical verdict definitions are justified because no output schema exists — each sentence carries information the caller cannot get elsewhere.

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 must convey the result space itself, and it enumerates all five verdicts with their meanings and the conditions under which each arises. Combined with the annotations covering the safety profile and 100% parameter coverage, an agent has everything needed to invoke and interpret this 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?

Schema description coverage is 100%, so all three parameters (url, skipWellKnown, includeEvidence) are already documented in the schema. The description adds no syntax or trade-off detail for skipWellKnown or includeEvidence (e.g. what 'five well-known probes' means for verdict confidence), so it does not exceed the baseline.

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?

Opens with a precise verb+resource: 'Given a URL, say whether an AI agent may fetch it, on what terms, and at what price.' The enumerated verdict vocabulary ('allowed', 'charged', 'blocked', 'unknown') makes the scope unmistakable. It never names the sibling tools (access_explain_verdicts, access_list_agents), so the differentiation is only implicit.

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?

Usage is implied rather than stated: the reader infers this is the pre-fetch permission check, and 'Refusals come back as findings' hints at how to interpret output. There is no explicit when-to-use, when-not-to-use, or pointer to access_explain_verdicts when the caller needs the reasoning behind a verdict.

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