Count business days between two ISO dates, excluding weekends and country holidays. Pure/offline; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| end | Yes | End ISO date (YYYY-MM-DD) | |
| start | Yes | Start ISO date (YYYY-MM-DD) | |
| country | No | ISO 3166 country code (default: US) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden. It adds useful context: 'Pure/offline; price 0.0 (free)' and explicitly defines that it excludes weekends and country holidays. However, it does not describe edge cases such as start/end inclusivity, invalid date handling, or behavior when start > end.
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 two sentences long, front-loaded with the core function, followed by a brief cost/offline note. Every sentence is informative and there is zero waste.
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?
This is a simple tool with full schema parameter descriptions and no output schema. The description explains what it does, cost, and offline nature, which is sufficient for an agent to invoke it correctly. Sibling tools are not required for completeness here.
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% — all three parameters (start, end, country) have descriptive text in the input schema. The description adds no additional parameter-level meaning beyond what the schema already provides, 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 states 'Count business days between two ISO dates, excluding weekends and country holidays' with a specific verb and resource. It clearly distinguishes from sibling tools like holiday_calendar_is_holiday (single date check), holiday_calendar_next_business_day (find next business day), and holiday_calendar_list_holidays (list holidays).
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 clearly implies its use case: computing business days between two dates, excluding weekends and holidays. However, it does not explicitly mention alternatives or when not to use it, though the purpose is obvious enough for an agent to select correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinguished by domain prefixes (e.g., bid_watch, grant_watch) and specific action verbs. However, the high number of similarly structured watch tools could still cause confusion, though descriptions clarify exact purposes.
Every tool follows a consistent `domain_subdomain_action` pattern with underscores, e.g., `agent_audit_query`, `bid_watch_search`. Even long names like `commerce_catalog_agent_readiness_score` adhere to this structure.
With 147 tools, the server is far too broad, covering weather, carbon estimates, domain intel, and more—well beyond its stated 'Japan public-data ledgers' scope. This sheer volume overwhelms agents and dilutes focus.
The server offers many read-only tools for Japanese public data (bids, grants, licenses, etc.), but lacks create/update/delete operations for those domains. Additionally, numerous unrelated tools (e.g., carbon estimates, weather) feel tacked on, leaving gaps in core coverage.