analysis_tracking_consistency_check

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

With no annotations provided, the description carries the full burden and does it well. It explicitly discloses read-only behavior ('Read-only; reaches no platform API'), the shape of findings (severity, delivery_state, ad ids, evidence), the types of violations detected, the pre-flight mode behavior, default recognition of utm_* parameters, and the ads_without_readable_url fallback. No contradictions.

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 four sentences, each carrying distinct information: purpose+outputs, violation categories, read-only+API note, pre-flight usage, and parameter/edge-case behavior. It's appropriately sized for a complex tool but not as minimal as the calibrating example.

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 rich input schema descriptions and no output schema, the description still explains the return fields and covers edge cases. It could mention that comparisons never cross platforms and that ads are grouped by campaign_id, but those are already in the schema. Overall it's sufficient for an agent to decide to use it and understand what it will get.

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. The description adds meaning by explaining that planned_ads toggles pre-flight reporting and that utm_* parameters are recognized unless the convention declares more — details not in the schema. However, most parameter behavior is already well-documented in the schema, so it doesn't need to compensate much.

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 ('Audit') and resource ('final-URL tracking parameters across ad records you pass in') plus platform scope, and enumerates what findings it returns. It clearly distinguishes itself from platform-specific list/update siblings and other analysis_* tools by focusing on tracking-parameter consistency.

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?

It gives a concrete when-to-use trigger: 'Pass planned_ads to pre-flight ads before creating them — then only the new ads are reported.' It also states the tool is read-only and reaches no platform API, implying it can be used without side effects. However, it doesn't name specific alternatives or explicitly say when NOT to use it, so it stops short of a full 5.

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