get_company_officers

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It does not mention data freshness, pagination, error handling (e.g., invalid symbol), or any side effects. The mention of output formats is helpful but insufficient for a complete behavioral profile.

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 brief, front-loading the purpose in the first sentence. The docstring format (Args, Returns) adds structure but some formatting (pipes, literals) is unnecessary. Overall, nearly every element serves a function, though optional boilerplate could be trimmed.

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 no output schema, the description should explain return structure. It only says 'Returns: pd.DataFrame' which is minimal. For a tool with three parameters and complex output (likely multiple fields per officer), this is insufficient. The agent cannot infer data structure from this alone.

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 0%, so the description must compensate. It lists parameter names and types but only adds minimal meaning: 'toon is optimized for AI' for output_format. The semantics of 'filter_by' options ('working', 'all', 'resigned') are not explained, leaving the agent to guess. Score is above baseline because it at least enumerates options.

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 company officers for a given stock market symbol. It uses specific verbs ('Get') and a specific resource ('company officers'). Among many sibling get_* tools, 'officers' is distinctive and unambiguous.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, use cases, or when to choose different filter or output format values. The description simply states what the tool does without context for selection.

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