debug_data_layer

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 indicates a non-mutating 'Analyzes' operation and that recommendations are produced, but it does not describe return structure, side effects, or how the optional 'checkPoints' parameter changes behavior. This leaves significant behavioral ambiguity.

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, front-loaded sentence that immediately conveys the tool's main purpose. The marketing-style phrase 'Perfect for troubleshooting tracking issues' is somewhat extra, but the overall length is appropriate and the message is compact.

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 there is no output schema and no annotations, the description should explain what the tool returns and how 'checkPoints' affects the analysis. It does neither, leaving an agent without enough information to correctly interpret the tool's response or fully understand the optional parameter's role.

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?

The input schema already documents both parameters with descriptions, providing 100% coverage. The description adds some context about the kind of analysis performed ('missing variables, type mismatches'), which loosely contextualizes the 'dataLayer' input, but it does not add meaningful detail about 'checkPoints' beyond what the schema already states.

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 ('Analyzes') and names the resource ('data layer'), and goes on to specify the scope: common issues, missing variables, type mismatches, and recommendations. This clearly states what the tool does, though it does not explicitly distinguish it from the sibling 'validate_data_layer'.

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 phrase 'Perfect for troubleshooting tracking issues' gives a clear use case and implied context, but there is no explicit guidance on when to prefer this tool over sibling 'validate_data_layer' or when it should not be used. The selection guidance is largely implied rather than stated.

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