Oku-Akasaka Sushi Tanji

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

Beyond the readOnly/idempotent annotations, the description discloses that the tool never books, never takes payment, does not know free times, and refuses dates the restaurant has reported closed. These behavioral constraints are valuable and consistent with 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?

Four short sentences front-load the core purpose and then add user flow and limitations. Every sentence contributes new information and there is no redundant or filler wording.

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?

The description covers purpose, user flow, and constraints well for a link-generation tool with no output schema. It could be slightly more explicit about the exact return format (e.g., plain URL vs. structured result), but the opening 'Link to...' makes the intended output reasonably clear.

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 50%, so the description needs to compensate for the undocumented course and people parameters. It maps 'course, date and party size' to the preselected fields, but it does not explain the course enum values, the language parameter, or the people range beyond what the schema already conveys.

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 concrete statement: it returns a link to the restaurant's TableCheck booking page with course, date, and party size preselected. This is a specific verb-plus-resource and clearly differentiates the tool from the course-listing and recommendation siblings.

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?

It gives clear context that the tool is for generating a booking-page link where the guest chooses the time, and explicitly excludes booking, payment, and availability checks. It does not name the sibling tools as alternatives, so it stops short of full explicit routing.

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 cover readOnlyHint, idempotentHint, and destructiveHint, so the description does not need to restate safety. It adds useful context that prices include tax and service charge and that there are exactly three courses, which go beyond the schema. However, it does not describe output structure or other runtime behavior, which is acceptable given 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 one short sentence with no filler, conveying the core content and an extra detail about tax/service. It is front-loaded and efficient, though it slightly overlaps with the title. It earns its place by adding specificity about per-person pricing and inclusions.

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, one-parameter list tool, the description adequately explains what the agent will receive: courses, per-person price, inclusions, and tax/service. It does not explicitly mention output format or language behavior, but those are covered by the input schema. Since there is no output schema, the description serves most of the expectation-setting role and is nearly 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 schema fully documents the single lang parameter with enum values and default, so the baseline applies. The description adds no parameter-specific guidance about language selection or result formatting. With 100% schema coverage, the lack of additional parameter details is acceptable.

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 identifies the resource: the three courses with per-person price and inclusions. It is distinct in subject from siblings like get_booking_link, though it does not explicitly contrast itself. The lack of an explicit verb like 'lists' or 'returns' is mitigated by the tool name and title.

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 gives no guidance on when to use this tool versus its siblings get_booking_link or recommend_course. It implies that it is the source for course and pricing information, but it does not state exclusions or direct the agent to alternatives. This leaves selection logic entirely to inference.

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 destructiveHint=false, so the safety profile is covered. The description adds value by disclosing that the tool returns not just a recommendation but also a reason and the other courses, which is useful behavioral context beyond the schema and 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?

Two sentences with no filler. The first sentence front-loads the action and inputs; the second explains the return shape. Every sentence earns its place.

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 read-only recommendation tool with three fully documented parameters, the description explains the inputs, the output shape, and the fact that it returns alternatives. It could be slightly more complete by distinguishing itself from sibling tools, but nothing critical is missing for calling it 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 100%, so the baseline is 3. The description names two key inputs (budget and sake preference) in plain language but adds no new meaning beyond the schema; the lang parameter is only documented in the schema, which is acceptable given full coverage.

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 states a specific verb ('Suggest'), a resource ('a course'), and the exact inputs it uses (budget per person and sake preference). It also clarifies the return value (the suggestion, a reason, and the other courses), which distinguishes it from simply listing courses.

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 the tool is for when a guest needs a single course recommendation based on budget and sake preference, but it never explicitly says when to use this tool instead of get_booking_link or list_courses. There are no exclusions or alternative-routing hints, so the guidance is only implicit.

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