get_sector_performance

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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds behavioral context: 'All plans' and 'cache-only, no API call', which informs the agent about data freshness and plan availability. While it doesn't detail return structure, the output schema covers that. This goes beyond annotations without contradiction.

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 compact and well-organized: purpose sentence, usage keywords, alternatives, plan info, then arg definitions. No wasted words; front-loaded with the core purpose.

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 simple read-only data tool with 2 parameters, the description covers purpose, exact use cases, alternatives, plan restrictions, cache behavior, and parameter formats. Combined with annotations and output schema, it is complete.

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 has only titles and defaults, with 0% coverage, so the description carries the full burden. It explains date format (YYYY-MM-DD or YYYYMMDD) and sector_type options ('s33' default, 's17') clearly, making both parameters fully understandable.

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?

States precisely: 'Sector-level average price change ranking' with Japanese equivalent, and distinguishes itself from get_sector_briefing (valuation) and get_market_briefing (full market briefing). The verb 'get' plus resource and the ranking nature are clear.

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?

Explicitly lists use cases (業種別騰落率, セクター別パフォーマンス, etc.) and provides alternatives for different needs: 'For sector valuation (PER/PBR) use get_sector_briefing instead. For full market briefing use get_market_briefing instead.' This is exemplary guidance.

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