get_comparison_chart_data

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: 'cache-only, no API call' and details the return structure. No contradictions. The additional context on caching and output format raises the score above the baseline.

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 a clear purpose statement, bullet-pointed arguments, and return format. It is slightly long but every sentence adds value. Front-loads the key purpose and sibling differentiation.

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 5 parameters (3 required), 0 nested objects, and an existing output schema, the description covers all essential aspects: input constraints, return structure, plan info, and sibling alternative. It is fully self-contained and leaves no ambiguity for an AI agent.

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?

With 0% schema description coverage, the description fully compensates by explaining each parameter: codes (1-10 stock codes), from_date/to_date (formats), mode (options and default), and labels (optional, custom vs auto-generated). This adds significant meaning beyond the raw 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 it returns 'time-series data for a multi-stock comparison' and specifies usage for '比較チャート・パフォーマンス比較・リターン比較・relative performance queries'. It distinguishes from sibling tool get_candlestick_data, providing a specific verb+resource+scope.

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 explicit use cases and an alternative tool for candlestick charts. It mentions plan limits and code maximum (10). However, it does not explicitly state when not to use it beyond the sibling alternative, which is acceptable given the clear context.

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