get_dividend_data

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'fetches' data, implying a read-only operation, but doesn't clarify permissions, rate limits, error handling, or return format details. The mention of 'Dividend records table' hints at the output structure, but lacks specifics like columns or pagination. For a tool with 5 parameters and no annotations, this leaves significant behavioral gaps.

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 well-structured and concise, with a clear purpose statement followed by parameter details in a formatted 'Args' and 'Returns' section. Every sentence adds value: the purpose is front-loaded, and parameter explanations are efficient with examples and defaults. No wasted words 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 complexity (5 parameters, no annotations, no output schema), the description is incomplete. It covers the core purpose and some parameters but misses two parameters ('limit', 'format'), provides no output schema details beyond 'Dividend records table', and lacks behavioral context like error handling or data freshness. For a data-fetching tool with multiple parameters, this leaves the agent under-informed.

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 description adds meaningful context for 3 parameters (code, year, year_type) by explaining formats, examples, and valid options, which compensates partially for the 0% schema description coverage. However, it omits the 'limit' and 'format' parameters entirely, leaving them undocumented. With 5 total parameters and only 3 covered, the description provides moderate but incomplete semantic value beyond the bare schema.

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: 'Fetches dividend information for a given stock code and year.' It specifies the verb ('fetches'), resource ('dividend information'), and scope ('for a given stock code and year'). However, it doesn't explicitly differentiate from sibling tools like 'get_profit_data' or 'get_balance_data', which might also fetch financial data but for different metrics.

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 doesn't mention sibling tools like 'get_profit_data' or 'get_stock_basic_info', nor does it specify prerequisites or exclusions. The agent must infer usage from the purpose alone, which is insufficient for optimal tool selection.

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