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 provided, the description carries the burden and does a good job: it discloses pure/offline execution, free price, and the key behavior of skipping weekends and country holidays, plus negative offset handling. It does not detail return format or error cases, but covers the main behavioral traits beyond the schema.
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, tightly worded sentence with value-adding details (offset direction, holiday skipping, pure/offline, free). Every phrase earns its place and the main action is front-loaded.
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 3-parameter tool with no nested objects or output schema, the description covers purpose, key behavioral nuances, and cost/offline status. The only gap is not explicitly stating the return type (presumably a date string), but this is largely inferable from the tool's name and purpose.
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 adds no new parameter-level meaning beyond what the schema already says; 'N steps' and negative offset behavior are already in the offset parameter description. Thus it earns the baseline score.
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 computes the business day N steps from an ISO date, skipping weekends and country holidays, with negative offsets going backward. This specific verb+resource+scope distinguishes it from sibling tools like holiday_calendar_business_days_between (which calculates 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 description implies usage for stepping forward/backward from a date but does not explicitly state when to use this tool versus alternatives like holiday_calendar_business_days_between. It does add context that it is pure/offline and free, which helps in selection, but lacks direct comparison or exclusions.
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 have clearly distinct purposes, especially the ledger-watch groups with domain prefixes. However, there are near-duplicate utilities such as content_authenticity_domain_reputation and domain_intel_reputation, and fx_tax_convert overlaps with price_oracle_fx_rate/convert. The sheer number of tools also increases the chance of selecting the wrong one, though descriptions are generally clear.
The naming is largely consistent with a <domain>_<action> or <domain>_<watch>_<action> pattern, and all names use snake_case. Minor deviations include standalone names like entity_search, kyb_report, verify_receipt, and the confusing singular/plural pair of sanction_watch_* and sanctions_screen_*. Overall, the pattern is predictable.
With 172 tools, this server is far beyond the typical well-scoped range. It bundles dozens of unrelated utility domains (weather, carbon, CVE, geo, etc.) alongside the Japan public-ledger watches, making it unwieldy for an agent to navigate. This extreme count is a major coherence problem.
For the core Japan public-ledger domain, coverage is excellent: each ledger has search, get, timeline, recent_changes, and verify_ledger, plus cross-ledger entity_search and temporal_query. The unrelated utility areas are also fairly complete for their own purposes, but the server's scope is so broad that some utilities are duplicated (e.g., multiple currency converters). Overall, no critical dead ends in the main domain.