detect_consecutive_dividend_increase

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, but the description goes further by disclosing key behaviors: lookahead-free backtesting via as_of_date, sorted output by consecutive_years descending, return field details, and cache-only operation with no API call. It also adds an investment caveat about performance guarantees, which is valuable context beyond the annotations.

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 with front-loaded purpose, explicit usage guidance, supported plans, and clearly separated Args/Returns sections. Each sentence adds useful information, and the minor redundancy of 'All plans' followed by the supported plans list does not detract from overall efficiency.

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?

Despite having an output schema, the description still explains return fields and ordering, covers both parameters thoroughly, mentions supported plans and API behavior, and provides a realistic investment caveat. It is complete for an agent to decide when and how to invoke the tool correctly.

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%, but the description's Args section fully compensates by explaining min_years as 'Minimum number of consecutive years of dividend increase' and as_of_date as a cut-off date with format examples and lookahead-free semantics. This adds substantial meaning beyond the raw schema properties.

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 opens with a specific verb and resource: 'Screen for stocks with consecutive annual dividend increases (連続増配).' This clearly distinguishes the tool from siblings like get_dividend_yield_ranking and other detect_* screeners by focusing on consecutive growth rather than yield or price patterns.

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 explicitly states use cases ('Use for 連続増配・dividend growth・増配継続 queries') and provides a caution about not relying on dividend growth alone, suggesting combining with yield/payout filters. It does not name alternative tools or state explicit when-not conditions, but the context is clear enough for an agent to select it appropriately.

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