Paid ($0.01/call): Japan digital & financial regulatory events (crypto, AML/sanctions, tax, AI) in English, human-reviewed. Factual data; not investment or legal advice.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| since | No | ||
| category | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It usefully discloses the per-call cost, human-review status, factual nature, and a disclaimer (not investment/legal advice). Still, it omits practical behavioral details such as result ordering, pagination, expected update frequency, or any required permissions/authentication.
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 extremely concise, packing cost, geographic scope, topical scope, language, and review status into one sentence, plus a one-line disclaimer. It is front-loaded with the most operationally relevant detail (cost). No wasted words.
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?
The tool has no output schema, so the description should explain what the returned data looks like or at least how results are presented. It does not. It also leaves 'since' syntax and the semantics of the result set ambiguous. Given the sibling context and simple query nature, this is a notable gap.
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 input schema has no parameter descriptions, and the description provides zero explanation of 'limit', 'since', or 'category'. While the names are somewhat self-explanatory, the format for 'since' (e.g., ISO date?) and how the enum values map to events is unclear. The description does nothing to compensate for the 0% schema coverage.
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 identifies the resource as 'Japan digital & financial regulatory events' and specifies relevant domains (crypto, AML/sanctions, tax, AI). However, it lacks an explicit verb like 'list' or 'retrieve', so the action is implied rather than stated. It is sufficiently distinct from sibling tools (e.g., sanctions_check, get_terms) due to the event focus.
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 when Japan regulatory event data is needed, and it clearly notes it is a paid tool. However, it does not explicitly state when to use this versus alternatives, nor does it provide any exclusions or prerequisite context. The guidance is basic and inferred from the resource type.
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 distinct: catalog, terms, regulatory events, and sanctions check each have unique purposes. The two DEX spread tools are similar but differentiated by summary vs. anomaly, though they could cause minor confusion without careful reading.
Tool names mix conventions: 'catalog' and 'reg_events' are noun phrases, 'get_terms' uses a verb, and 'sanctions_check' is a noun phrase with a verb component. All use snake_case, but there is no consistent verb_noun pattern across the set.
Six tools is a well-scoped number for a data-provider server, covering catalog, terms, and several distinct data products without being bloated or thin.
The surface covers the core functionality: discovering data via catalog, understanding terms, accessing regulatory events, DEX summaries/anomalies, and doing sanctions checks. Minor gaps exist (e.g., no tool for raw DEX spread data or detailed event lookup), but the main workflows are supported.