Determine whether an ISO date is a public holiday for a country (US/GB/JP/DE) from a built-in rule-based dataset; returns the holiday name when matched. Pure/offline; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | 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?
No annotations are provided, so the description carries the full burden. It discloses that the tool is pure/offline, free, uses a built-in rule-based dataset, and only supports specific countries. This adds meaningful behavioral context beyond the schema, though it does not detail error handling or exact return schema for non-matching dates.
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 main purpose, and contains no redundant information. Every sentence adds relevant detail about functionality, supported countries, return behavior, and operational characteristics.
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 check tool, the description covers purpose, supported inputs, return behavior (holiday name when matched), and operational traits (offline/free). The schema provides parameter details, and no output schema exists, but the return description is sufficient for the tool's simplicity.
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 already describes both parameters with 100% coverage, so baseline is 3. The description adds value by specifying the supported country codes (US/GB/JP/DE) and reinforcing the ISO date format, which clarifies constraints not fully evident from the schema alone.
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 determines whether an ISO date is a public holiday for a country (US/GB/JP/DE) and returns the holiday name when matched. This specific verb+resource scope distinguishes it from sibling tools like holiday_calendar_list_holidays and holiday_calendar_business_days_between.
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 single-date holiday checking via its wording, but it does not explicitly mention when to use it instead of alternatives or provide exclusion criteria. There is no reference to sibling tools or conditions like 'for checking multiple dates, use list_holidays'.
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.