SEO·AEO·GEO

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

Annotations only declare readOnlyHint and openWorldHint; the description goes much further, disclosing the fetch identity (OAI-SearchBot, Claude-SearchBot, PerplexityBot), what failure modes are surfaced (robots.txt, CDN and firewall blocks), that no-JS content volume is measured, and the 10–30 second runtime. That is exactly the kind of behavior an agent cannot get from structured fields.

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?

Four sentences, front-loaded with the action and targets, then method, then return shape, then runtime. Every sentence carries distinct information with no repetition of the schema or title.

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?

There is no output schema, and the description compensates by enumerating the return payload: the score, every check's result, and a priority-ordered fix pack with codebase locations and verification commands. For a two-parameter read-only tool with annotations, nothing material is left unspecified.

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 both `url` and `question` are already documented, including the note that `question` adds fit analysis without changing the score. The prose only reinforces the single-page scope and adds no new parameter semantics, so the baseline 3 applies.

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 verb and resource ('Audit one public web page') plus the exact scope of what is measured (Google, AI Overviews, ChatGPT, Claude, Perplexity). It never names the sibling get_report, so the agent must infer the split between running an audit and retrieving a report; otherwise the purpose is 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?

'Audit one public web page' and 'Takes 10–30 seconds' give clear selection context, including a latency expectation an agent can use to decide whether to call it inline. No explicit when-not-to-use or named alternative (get_report) is offered, so it stops short of full routing guidance.

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

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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds a meaningful operational constraint not in structured data: only audits from the last 24 hours are retrievable, which tells the agent when the call will fail. It also names the returned artifacts (summary and fix pack).

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?

A single front-loaded sentence that states the action, the returned content, the retrieval window, and the keying parameter with no wasted words.

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 one-parameter read tool with no output schema, the description covers the essentials: what is returned (summary and fix pack) and the 24-hour retention limit. It is nearly complete, missing only explicit routing to the audit_url sibling.

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?

Only one parameter with 100% schema coverage; the schema already documents report_id and its origin from audit_url. The description restates 'by its report id' without adding format or validation detail, so the baseline 3 applies.

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 verb and resource ('Return the summary and fix pack of an audit run'), which is concrete and distinguishable from the sibling audit_url that produces the id. The scope qualifier ('in the last 24 hours') further narrows it, though it doesn't explicitly name audit_url as the counterpart tool.

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: retrieve an audit run's results by id, where the id comes from audit_url. However, there is no explicit when-to-use/when-not statement, and the relationship to the sibling is left to the schema's parameter note rather than stated in the description.

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