run_aeo_audit

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: the operation is asynchronous ('async'), returns an auditId immediately, and has tier-based limitations (free tier stops at step 2). It also implies rate limits or polling intervals ('every 10–15s'). However, it doesn't detail error handling, timeouts, or authentication needs, leaving some gaps.

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 highly concise and well-structured: two sentences that front-load the core action and immediately follow with essential usage instructions. Every sentence earns its place by providing critical operational details without redundancy or fluff.

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 (async operation with polling) and lack of annotations or output schema, the description is largely complete. It covers the async nature, return value (auditId), polling requirements, and tier limitations. However, it doesn't explain what 'step 2' entails or potential errors, leaving minor gaps for an agent to handle 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?

Schema description coverage is 100%, so the schema already documents all parameters (url, keyword, tier) with descriptions and defaults. The description adds no additional parameter semantics beyond what's in the schema, such as explaining keyword selection impact or tier implications in more depth. Thus, it meets the baseline but doesn't enhance understanding.

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 tool's purpose: 'Start an AEO audit for a URL (async).' It specifies the action ('Start'), resource ('AEO audit'), and scope ('for a URL'), distinguishing it from sibling tools like check_aeo_audit_status or generate_aeo_content_suite by focusing on initiating an audit rather than checking status or generating content.

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 explicit usage guidance: it instructs to 'call check_aeo_audit_status every 10–15s until is_complete or free_preview_ready' and notes that 'free tier stops at step 2.' This gives clear when-to-use context (start audit, then poll) and distinguishes from alternatives by implying this is the entry point for audits, with check_aeo_audit_status as the follow-up.

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