company_dividends
Retrieve dividend data for publicly traded companies to analyze shareholder returns and company financial performance.
Instructions
Fetch company splits
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes |
Retrieve dividend data for publicly traded companies to analyze shareholder returns and company financial performance.
Fetch company splits
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'Fetch' implies a read operation, but the description provides no information about authentication requirements, rate limits, error conditions, response format, or whether this is a real-time or historical data source. This is inadequate for a tool with no annotation coverage.
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 extremely concise at just two words. While this represents under-specification rather than ideal conciseness, it's not verbose or poorly structured. Every word serves a purpose, even if that purpose is insufficient.
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 financial data tool with no annotations, no output schema, and 0% parameter documentation, the description is completely inadequate. It doesn't explain what data is returned, in what format, with what limitations, or how it differs from related tools. The name/description mismatch further undermines completeness.
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 input schema has 0% description coverage, with one required parameter 'symbol' completely undocumented. The description adds no information about what the symbol parameter represents (ticker format, exchange codes, validation rules) or how it should be used. This fails to compensate for the schema coverage gap.
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 'Fetch company splits' restates the tool name 'company_dividends' without clarifying the actual purpose. The name suggests dividends while the description mentions splits, creating confusion rather than providing a clear verb+resource statement. This is a tautology with misleading elements.
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. With many sibling tools available (like company_earnings, company_overview, balance_sheet), there's no indication of what distinguishes this tool or when it's appropriate to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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