Compute the business day N steps from an ISO date, skipping weekends and country holidays (negative offset goes backward). Pure/offline; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | ISO date (YYYY-MM-DD) | |
| offset | No | Number of business days to step (default: 1; negative goes backward) | |
| country | No | ISO 3166 country code (default: US) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It adds useful context: 'Pure/offline; price 0.0 (free)' and explicitly says it skips weekends and country holidays with negative offsets. However, it doesn't disclose return format, boundary semantics (whether the starting date counts as day 0), or the holiday data source.
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 concise sentences, front-loaded with the core operation. The first sentence explains what and how, the second adds cost/offline context. Every word earns its place without unnecessary fluff.
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 compute tool with three well-documented parameters, the description is largely complete. It covers the core function, offset direction, holiday handling, and cost. The lack of output schema is mitigated by the clear 'Compute the business day' phrasing. Minor gaps like exact return format or edge-case behavior are not critical.
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 reinforces the offset behavior ('negative offset goes backward') which is already in the schema, but adds little meaning beyond that. Parameter details like country defaults are already in the schema, so the description doesn't compensate further.
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 function: 'Compute the business day N steps from an ISO date, skipping weekends and country holidays.' It specifies the resource and operation with enough detail to distinguish it from siblings like holiday_calendar_business_days_between (which counts days between two dates) and holiday_calendar_is_holiday.
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 use case is implied by the description ('business day N steps from an ISO date'), but it doesn't explicitly say when to choose this over alternatives, nor does it name sibling tools like holiday_calendar_business_days_between for counting business days between two dates. This is adequate but not proactive guidance.
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.