HoShy

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

Annotations already declare readOnlyHint=true, and the description adds meaningful behavioral context: it ranks results by effective price including shipping and point rebates. This goes beyond the annotation and helps the agent understand how results are ordered. No contradictions.

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 a single, concise sentence that front-loads the core purpose and includes the key ranking behavior. Every word earns its place, with no redundant information.

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 straightforward read-only price comparison tool, the description covers purpose and output ranking logic. However, since there is no output schema, it doesn't specify the exact return structure or error behavior. This is a minor gap, but the tool is simple enough that the description is mostly 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?

The input schema has 100% coverage with all parameter descriptions. The description adds no additional parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 compares lowest prices on Rakuten Market by product name/model number, with a specific verb (比較) and resource (楽天市場). This distinguishes it from sibling tools like recommend_for_consumer and search_business_hotel.

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 clear context: use when you need to find the cheapest price for a specific product on Rakuten. It does not explicitly mention alternatives or when-not-to-use, but the sibling tools are clearly different in purpose, so the usage context is unambiguous.

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

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

With readOnlyHint annotation already present, the description adds meaningful behavioral context: it returns the top 5 items ranked by effective price after points and review rating, and budget is used as a prioritization factor. It does not contradict the annotation or introduce additional behavioral caveats.

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 consists of one tightly worded sentence that delivers the action, criteria, and result in a front-loaded, efficient manner. Every phrase earns its place with no 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 tool's moderate complexity (4 params) and lack of an output schema, the description covers the essential behavior: search basis, ranking criteria, and result count. It doesn't enumerate specific return fields, but for a recommendation tool this is reasonably 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 coverage is 100%, so the baseline is 3. The description adds limited value beyond the schema: it highlights keyword and budget as core inputs but does not mention hits or spu_rate explicitly, though the ranking logic implies their use. The schema itself already documents these parameters adequately.

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 a specific verb '探します' (search) with a defined resource '楽天市場' and a clear scope (keyword and budget). It distinguishes from sibling tools like compare_prices and search_business_hotel by focusing on product recommendations using rating and effective price.

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 implies when to use the tool (when looking for recommended products based on keyword and budget) but provides no explicit exclusions or alternatives. It lacks direct guidance on when to prefer this over sibling tools, leaving usage context implied.

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

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

Annotations already declare readOnlyHint=true, and the description does not contradict this. It adds a useful behavioral detail—that it calculates actual travel time via Google Maps to filter results—which goes beyond simple read operations. Still, it doesn't discuss potential external API dependencies or result format, so the added transparency is moderate.

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 a single, information-dense sentence that front-loads the tool's purpose and method. It contains no filler words, making it easy for an agent to parse quickly.

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 tool with 8 parameters and no output schema, the description explains the core functionality and the unique travel-time filtering logic. However, it does not describe the return value or result structure, which could leave agents uncertain about the response format. The rich schema and annotation mitigate some gaps, but the missing output details prevent a higher score.

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 provides full descriptions for all 8 parameters, including examples and constraints, so the schema already carries the semantic load. The description mentions the key parameter groups (destination, schedule, budget, travel time) in prose, which reinforces but does not add meaning beyond the 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 searches for business hotels on Rakuten Travel using destination, schedule, budget, and travel time constraints. It uses a specific verb ('search') and resource ('business hotels'), which distinguishes it from sibling tools like compare_prices and recommend_for_consumer.

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 clear context for when to use the tool: when searching for hotels based on destination, dates, budget, and travel time. However, it does not explicitly mention when not to use it or name alternative tools, so it stops short of full usage guidance.

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