efactura_messages_get

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

No annotations are provided, so the description carries disclosure burden. It reveals the tool returns both parsed details and raw ANAF response data, and includes related invoice information when available. This is helpful behavioral context, though it doesn't disclose details like error behavior for unknown UUIDs, auth requirements, or rate limiting.

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?

Three concise sentences with zero waste. The first sentence states the core purpose, the second adds value about included related data, and the third gives a concrete use case. Perfectly front-loaded and appropriately sized for a single-parameter retrieval tool.

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 single-parameter getter with 100% schema coverage and no output schema, the description adequately explains what data is returned (parsed details, raw ANAF data, related invoice info) and a use case. No output schema means it can't lean on that for completeness, but the description's disclosure of return content compensates well.

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% — the single 'uuid' parameter is fully documented in the schema as 'UUID of the e-Factura message to retrieve.' The description adds no additional meaning about the parameter format or constraints beyond the schema, so baseline 3 is appropriate since the schema does the heavy lifting.

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 clearly states the tool retrieves full details of a specific e-Factura message including parsed details and raw ANAF response data. It distinguishes itself from the sibling efactura_messages_list (which lists messages) by being the detail-retrieval counterpart. The verb+resource+scope pattern is specific and clear.

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 explicitly notes it's 'useful for diagnosing specific invoice upload errors,' giving a clear use case. However, it doesn't explicitly say when NOT to use it or name the alternative (efactura_messages_list); differentiation is implied by the name and the 'full details' framing rather than stated explicitly.

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