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 explains that the data comes from 'fixed-window rollups', is 'complete-population', includes 'bounded page details', and emphasizes the non-additive nature of lift. This provides meaningful context about how the tool behaves without relying on structured metadata.

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 two sentences with no redundancy. The main purpose is front-loaded, and the second sentence adds an essential nuance about the nature of the lift metric. Every phrase earns its place without any filler.

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?

The description explains the domain-specific concepts of 'Direct lift' and clarifies its relationship to measured referrals, which is crucial for correct usage. However, since there is no output schema, it does not describe the return structure beyond 'bounded page details', which is a minor gap given the overall clarity.

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% and both parameters (pageLimit, windowDays) already have descriptive text in the schema. The description adds no extra meaning to the parameters beyond what the schema provides, only indirectly referencing 'bounded page details' and 'fixed-window rollups'. This matches the baseline for high schema coverage.

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 uses a specific verb 'get' and names the exact resource: 'complete-population GA4 Direct traffic and resolver-owned AI-correlated lift classifications'. It clearly distinguishes this from siblings by explaining it is 'correlated evidence, not attributed traffic' and 'never added to measured referral totals', which sets it apart from tools like get_ai_referrals or get_traffic_summary.

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 a clear when-not by stating the output is 'never added to measured referral totals', implying it should not be used for referral attribution. It also clarifies the semantic of 'lift' as correlated evidence, which guides selection. However, it does not name any specific sibling tools or give explicit conditions for when to use this over alternatives.

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