Look up the sales-tax rate for a region from built-in tables and, if an amount is given, compute net/tax/gross. Pure; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| amount | No | Optional amount to compute tax on | |
| region | Yes | Region key with a sales-tax rate on file (e.g. US-CA) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It adds 'Pure; price 0.0 (free)' and 'from built-in tables', which are useful. However, it does not describe behavior for invalid region keys, whether tax is inclusive/exclusive, rounding rules, or error handling, leaving some ambiguity for the agent.
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, front-loaded with the primary purpose, and every clause earns its place. 'Pure; price 0.0 (free)' is a concise but meaningful behavioral note. No redundancy or filler.
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 tool with two well-described parameters, the description covers the main purpose, optional computation, and a key prerequisite (populating rates via fx_tax_list_rates). It does not specify the exact return structure, but given no output schema, some output details are implied by 'net/tax/gross'. The description is adequate but omits potential edge cases like unknown regions.
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 context by explaining the parameters' role in the computation ('if an amount is given, compute net/tax/gross' and 'region with a sales-tax rate on file'), but it does not provide additional syntax, value formats, or examples beyond what the schema already specifies.
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 a specific verb ('look up' and 'compute') with a specific resource ('sales-tax rate for a region') and distinguishes this tool from siblings like fx_tax_vat_calc (VAT) and fx_tax_convert (currency conversion). It also mentions the optional computation of net/tax/gross, making the tool's purpose unambiguous.
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 explicitly instructs to 'Populate the rates table first using fx_tax_list_rates', which provides a clear when-to-use and prerequisite. It also implies alternatives by specifying this is for sales tax from built-in tables, contrasting with VAT or other tax tools, and the 'Pure; price 0.0' hints it is a free lookup/compute with no side effects.
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.