get_account_info

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

No annotations are provided, so the description carries the full burden. It describes what information is returned but does not disclose behavioral traits such as authentication requirements, rate limits, error conditions, or whether the data is real-time or cached. For a tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves operationally.

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 two sentences, front-loaded with the core purpose and followed by a usage hint. Every sentence adds value: the first specifies what the tool does and what data it returns, and the second provides context for when it might be useful. There is no wasted text or redundancy.

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 tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is reasonably complete. It explains the purpose and the type of data returned, which aligns with the output schema's role. However, without annotations, it lacks details on behavioral aspects like authentication or performance, which could be important for a read operation in an account context.

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 tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description does not need to add parameter semantics, and it appropriately focuses on the tool's purpose and output. A baseline of 4 is applied as it meets expectations for a parameterless tool.

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's purpose: 'Provides the current user's Sauce Labs account information' with specific details like 'username, jobs run, minutes used, and overall account status'. It uses a specific verb ('Provides') and resource ('account information'), but does not explicitly differentiate from sibling tools like 'get_user' or 'get_my_active_team', which might provide overlapping or related user/account data.

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 'Useful for a quick overview of account activity', which implies usage context for monitoring account status. However, it does not specify when to use this tool versus alternatives like 'get_user' or 'get_my_active_team', nor does it provide exclusions or prerequisites. The guidance is implied but not explicit.

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