get_company_reports

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains the output format options and notes that 'toon' is optimized for AI, which is helpful. However, it does not disclose whether the operation is read-only, any potential latency, or side effects. Basic transparency is provided but not comprehensive.

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 with a clear structure: purpose line, then 'Args:' section, then 'Returns:' section. It avoids unnecessary words. The only minor issue is that the 'Args' listing repeats schema info, but it is well-organized.

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?

The description explains the output is a DataFrame but does not describe the columns or content of the reports. Given the tool's complexity (simple parameters, no output schema), it leaves gaps about what data is actually returned. For instance, does it return one report or multiple? No information about the structure of the reports. Thus, it is incomplete for confident use.

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 0%, so the description must add meaning beyond the raw schema. It explains the 'output_format' enum values, highlighting 'toon' as optimized for AI, which adds value. However, for 'symbol', it only notes it is a string, adding no further context. The semantics are partially enhanced but not fully compensated for the lack of schema coverage.

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 reports from the stock market. The verb 'Get' and resource 'company reports' are specific. However, it does not differentiate from sibling tools like get_company_overview or get_company_ratio_summary, leaving ambiguity about what kind of reports are returned.

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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, typical use cases, or exclusions. The agent must infer usage from context, which is insufficient.

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