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

With no annotations, the description carries the behavioral disclosure burden. It discloses the key deduplication behavior—events are deduplicated by the event_id + event_type combination—and frames the event as an attribution record. It does not specify response/error behavior or exact duplicate-handling semantics (first-wins vs last-wins), so it is not a 5.

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 front-loaded with the core purpose, followed by a compact dedup note, scannable use-case bullets, and a single illustrative example. Every section earns its place; no filler or redundant restatement.

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 nested event object and no output schema, the description is largely complete: it covers purpose, when to use, dedup behavior, and a realistic invocation example while the schema documents each parameter. The main gap is that it does not describe what the call returns or how duplicate events are resolved, which prevents a 5.

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 baseline is 3, but the example adds concrete invocation value: it shows how to nest the event object, populate media_buy_id, provide event_id/event_type, and attach free-form metadata. This goes beyond the schema's type-level descriptions and reduces ambiguity for an agent.

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 opens with a specific verb and resource: 'Record a conversion or attribution event', then clarifies its purpose as 'post-campaign attribution analysis'. This clearly differentiates it from sibling tools like record_impression, which targets impression events rather than conversion/attribution events.

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 'WHEN TO USE' section lists concrete scenarios: offline conversions, post-view attribution, and custom KPI events. It gives clear context for when the tool applies, though it does not explicitly name alternative sibling tools or state when not to use it.

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