AEO Audit

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

With no annotations, the description must disclose behavioral traits. It only states it runs an audit and returns metrics but does not mention if it is read-only, requires authentication, has rate limits, or any side effects. The description is minimal in behavioral transparency.

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 description is concise with two sentences, front-loading the main action and outputs. Every sentence adds value with no redundancy.

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?

Given the tool's complexity (4 params, no output schema), the description adequately explains the return values (citation rate, grade, etc.). However, it lacks details on execution time, authentication needs, or whether the audit is real-time. Completeness is adequate but not thorough.

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 the description does not need to add parameter details. However, it adds context by explaining that queries are used to test the domain and that competitor comparison is returned, aligning with the competitors parameter. No syntax or format details are added beyond schema.

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 clearly states the verb 'run' and the resource 'domain' for a full AEO audit. It specifies the actions (checks appearance across AI answer engines) and outputs (citation rate, grade, competitor comparison, per-query results). This distinguishes it from siblings like quick_check (lighter) and audit_domain_premium (more detailed).

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 this is for a comprehensive audit but does not explicitly state when to use it versus alternatives like quick_check or suggest_queries. It lacks usage context, exclusions, or prerequisites.

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?

No annotations provided, so description carries full burden. It discloses the paid nature, lists outputs, and notes it is an enhanced version of audit_domain. No mention of authentication, rate limits, or side effects, but the core functionality is transparent.

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 description is concise yet comprehensive, front-loading the purpose and then listing key differentiators and pricing. Every sentence adds value without redundancy.

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?

Given no output schema, the description adequately outlines return values (recommendations, guide, gap analysis, score improvements). It references the base tool and sibling context. Missing details on authentication or prerequisites, but sufficient for an agent to understand usage.

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 100%, so the description adds minimal value beyond schema descriptions. It provides context that the tool builds on audit_domain but does not detail how each parameter influences the result.

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 clearly states it is a premium AEO audit that includes everything in audit_domain plus additional features. It distinguishes itself from siblings by listing specific premium offerings (actionable recommendations, implementation guide, competitive gap analysis).

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 usage for users wanting premium features beyond audit_domain, and includes pricing context. However, it does not explicitly state when to avoid this tool or provide direct comparisons with alternatives like quick_check or suggest_queries.

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?

No annotations are provided, so the description bears full burden. It only says 'visibility check' without clarifying whether this operation is read-only, what side effects occur, or how results are returned. Critical behavioral details are omitted.

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 description is a single concise sentence that immediately conveys the tool's purpose. No redundant words; it front-loads the key information.

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?

While the tool is simple, the description lacks information about the output format or how to interpret results. With no output schema, the agent needs behavioral clues that are missing. It is adequate but not complete.

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 67% (query and domain described). The description adds no additional meaning beyond the schema. The 'provider' parameter lacks a description in both schema and tool description, leaving its purpose unclear.

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 clearly states it performs a 'single-query AI visibility check for a domain.' This is a specific verb-resource pair that distinguishes it from sibling tools like 'audit_domain' and 'suggest_queries' by emphasizing speed and single-query nature.

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 usage for quick checks but does not explicitly state when to use this tool versus sibling audit tools or provide any prerequisites or exclusions. The agent can infer, but guidance is missing.

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?

No annotations provided, and the description lacks any behavioral details such as API usage, rate limits, authentication, or what the tool actually does behind the scenes.

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?

Single sentence is concise but lacks structure and fails to include necessary details. While brevity is good, it sacrifices completeness.

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?

Given 4 parameters, no output schema, no annotations, and sibling tools, the description is severely incomplete. No information about return values, usage context, or edge cases.

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?

With 0% schema description coverage and no parameter explanations in the description, the four parameters (count, domain, industry, language) are completely undocumented. The description only mentions domain/industry vaguely.

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 clearly states it generates AEO audit queries for a domain/industry, using a specific verb and resource. It distinguishes from sibling tools like audit_domain which likely perform audits rather than generate queries.

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?

No guidance on when to use this tool versus siblings like audit_domain or quick_check. No prerequisites, context, or alternatives mentioned.

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