PlugRail Japanese Calendar

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

With no annotations, the description fully covers behavioral aspects: it returns a date string, excludes weekends and Japanese holidays, optionally excludes banking holidays, allows custom extra closed dates, and clarifies that days=0 is not allowed. It also explains the counting direction for negative days.

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 paragraph but well-structured: it leads with the core logic, then special cases, then calendar options, then a tip for an alternative, and finally an example. Every sentence is necessary and informative without 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 4 parameters, no output schema, and moderate complexity, the description is complete. It covers all execution details, parameter constraints, calendar variations, and provides an example input. It also differentiates from sibling tools, though it could explicitly mention return format, which is implied.

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?

Although schema coverage is 100%, the description adds significant meaning beyond the schema: it clarifies that the start date is not counted, days=0 is invalid with suggested alternatives, and provides examples for date and extra_closed_dates. This enriches agent understanding.

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 the Nth business day after or before a given date, not counting the start date. It mentions the exclusion of weekends and Japanese holidays, and distinguishes itself from the sibling tool 'is_holiday' by advising to use that tool for checking if a date is a business day.

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 explicitly tells when to use this tool (to add or subtract business days) and when not to (use 'is_holiday' if only checking if a date is a business day). It provides an input example and explains the behavior for negative days, giving clear context for appropriate usage.

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 no annotations, the description fully discloses behavior: default inclusion/exclusion of boundaries, calendar parameter effects, holiday exclusions (weekends, Japanese holidays, banking holidays), and error on negative range. All key behavioral aspects are covered.

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 three sentences, front-loaded with the core purpose. It is informative without being verbose. A slight improvement could condense some details, but overall it is efficient.

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 all necessary aspects for a counting tool: inputs, defaults, error conditions, and special parameters. However, it does not explicitly state the return type (integer), though it is implied. Given no output schema, this is a minor gap.

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 parameters are documented in schema. The description adds value by explaining default values for include_from/include_to, providing an input example, and clarifying the effect of calendar and extra_closed_dates. It adds context beyond 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 counts business days between two dates, specifies default boundary behavior (include to, exclude from), and provides an example. It distinguishes itself from sibling tools (add_business_days, is_holiday, list_holidays) by the counting action.

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 explains when to use the tool (counting business days) and provides boundaries for from/to and error conditions (from > to). It does not explicitly compare to siblings or state when not to use, but the context and name make it clear.

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 no annotations, the description must fully disclose behavior. It only mentions data source but omits return value format, error handling for invalid dates, or update frequency.

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 sentence with a clear example, no redundancy, and front-loads the 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 single-parameter tool without output schema, the description covers the core function and data source but lacks return value type and error handling info, making it moderately 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 covers 100% of the parameter with format and example. The description adds an input example but no new semantics beyond the schema, so baseline 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 specifies the tool's function: determining if a given date is a Japanese holiday. It also states the data source (Cabinet Office) and distinguishes from siblings like list_holidays by focusing on a single date.

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 usage for checking a single date but does not explicitly compare with sibling tools (add_business_days, business_days_between, list_holidays) or provide when-not-to-use guidance.

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?

No annotations are present, so the description must disclose behavioral traits. It only states it returns a list; it does not mention that it is read-only, has no side effects, or any constraints like rate limits or required authentication.

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?

One sentence with embedded examples, no redundant information, and clear front-loading of 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?

The description lacks output structure details. With no output schema, the agent is left guessing the format of the returned holiday list (e.g., dates, names), which is critical for downstream use.

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 schema already documents all three parameters. The description adds example values but no additional semantic nuance 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 it returns a list of Japanese holidays for a specified year or period, with example inputs, and effectively distinguishes itself from siblings that deal with business days or single-date checks.

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 covers the primary use case (listing holidays by year/period) but does not explicitly exclude alternatives or mention conditions like when to prefer is_holiday.

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