Japan payroll suite: net salary + social insurance + income walls (+bonus) in one call. Flat $0.05.
| Name | Required | Description | Default |
|---|---|---|---|
| age | No | ||
| x_payment | No | Optional: base64 X-PAYMENT header value (x402 exact scheme, USDC on Base mainnet). Omit it to receive the payment requirements (accepts[] + docs) for this call without being charged. | |
| dependents | No | ||
| prefecture | Yes | ||
| annual_bonus_yen | No | ||
| annual_gross_yen | Yes | ||
| previous_month_after_si_yen | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden, but it only discloses the flat $0.05 price. It does not explain that omitting x_payment may produce payment requirements instead of computed payroll results, what the return shape is, or what assumptions/limitations apply.
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 short and front-loaded, mentioning core capabilities and pricing in two sentences. It loses some points because 'Japan payroll suite' mostly echoes the tool name and the terseness causes gaps in clarity and behavioral guidance.
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 complex 7-parameter computation tool with nested objects and no output schema, but the description gives no output format, calculation basis, input requirements beyond the required schema, or payment flow. The x_payment behavior in the schema hints at an important conditional flow that the description does not clarify.
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 only 14%, and the description barely compensates. annual_gross_yen, prefecture, dependents, age, and previous_month_after_si_yen are not semantically explained; only x_payment has schema-level context. The description's broad terms do not clarify how the parameters interact.
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 what the tool covers: net salary, social insurance, income walls, and bonus in a single call. This distinguishes it from sibling tools like jp_payroll_net, jp_social_insurance, and jp_bonus_net, though it is phrased as a label rather than a clear verb 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?
There is no explicit guidance on when to use this tool versus the more granular sibling tools. 'In one call' weakly implies a combined path, but it never explains when to choose this suite over jp_payroll_net, jp_social_insurance, or the other dedicated tools.
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.
Multiple tools have unclear boundaries: document_pipeline and parse_document both parse PDFs, portrait_analysis and style_profile both perform color analysis, enrich_company and jp_company_profile both resolve company profiles, and jp_payroll_suite bundles capabilities that already exist as separate tools. Descriptions are detailed, but an agent must carefully compare several near-synonyms before selecting.
All names are snake_case, but the conventions are mixed: get_* for metadata, jp_* for Japan-specific calculations, pdf_* for PDF operations, plus standalone nouns like meal_vision and style_profile. The prefixes help readability, but there is no uniform verb_noun pattern and ordering is inconsistent (quote_parse vs parse_document).
35 tools is far above the well-scoped 3-15 range and indicates an aggregator/marketplace rather than a focused server. Even with clear individual descriptions, the sheer breadth across OCR, PDF, Japan tax, style, and marketplace functions makes the tool set feel heavy and harder to navigate.
Within its broad marketplace scope, the server is fairly complete: paid products have free samples (get_sample), quotes (quote_parse), receipt retrieval (get_receipt), and discovery via get_catalog and search_x402_services. PDF and Japan tax coverage are extensive, though the wide domain spread means no single area feels fully exhaustive.