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

The description adds value beyond the readOnlyHint annotation by specifying that the tool returns status fields (lastSuccessfulSync, currentStatus, dataType) per accounting data type. It does not contradict annotations; it enriches them with behavioral detail. No annotation contradiction.

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 concise (two sentences) and front-loads the core purpose. It includes the API endpoint as supplementary context without unnecessary elaboration. Every word serves a purpose.

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?

For a simple status-check tool with a single parameter and no output schema, the description adequately conveys what it returns and when to use it. It does not describe return format or error handling, but given the tool's simplicity, it is sufficiently complete.

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% for the single parameter companyId, and the schema already describes it as a UUID. The description does not add additional semantics about the parameter, so it meets the baseline expectation but does not exceed it.

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 explicitly states the tool's function: 'Get the freshness/status of each accounting data type for a company' and lists specific fields (lastSuccessfulSync, currentStatus, dataType). This clearly distinguishes it from sibling tools that retrieve actual data (e.g., codat_get_invoice) rather than status.

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 includes a clear use case: 'Use this to check whether a dataset has been pulled before reading it.' This provides context for when to invoke the tool. However, it does not explicitly mention when not to use it or name alternative tools, so it loses one point.

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