Price list
pricingEvery endpoint this server fronts, with its exact per-call USD price (x402, USDC on Base) and a one-line summary, read live from the route table. Free.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
pricingEvery endpoint this server fronts, with its exact per-call USD price (x402, USDC on Base) and a one-line summary, read live from the route table. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that data is 'read live from the route table' (read-only, dynamic) and 'Free' (no cost). It could mention output format or rate limits, but for a simple listing tool, this is adequate transparency.
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, efficient sentence followed by 'Free.' It packs endpoint list, price, currency, summary, and live-read behavior with zero wasted words. Every part contributes to understanding the tool.
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 tool with no parameters and no output schema, the description is quite complete. It says 'every endpoint' and explains exactly what is returned (price and summary). It doesn't specify output format or authentication, but those are non-critical for this simple list tool. The sibling context further clarifies its niche.
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 zero parameters, so the baseline is 4. The description adds value by clarifying what the returned data will contain (prices and summaries), but since there are no params to document, it doesn't need to compensate.
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 what the tool does: it returns every endpoint with its exact per-call USD price, currency (x402/USDC on Base), and a one-line summary. It distinguishes itself from sibling data tools by focusing solely on pricing, and the verb 'lists' is implied by 'Every endpoint... with its exact per-call USD price'.
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 strongly implies this is the reference to consult before calling paid endpoints, especially with 'Free' indicating no cost. It doesn't explicitly name alternatives or say 'use before any paid call', but given it's the pricing list, the usage context is clear. No exclusions are needed.
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.
Each tool targets a distinct resource type (crypto address, domain, email, IBAN, phone, URL, vessel, entity name) or a distinct purpose (pricing, data discovery, data request). Overlapping sanctions tools are clearly differentiated by target: address_screen for addresses, sanctions_screen for names, vessel_screen for vessels, and sanctions_entity for detailed records after screening.
Most data-check tools follow a consistent object_verb pattern (e.g., address_screen, email_check, phone_check). However, find_data and request_data invert the order, domain_intel uses a noun instead of a verb, and pricing stands alone as a gerund, creating mixed conventions.
12 tools is well within the ideal range for a data-screening server. Each tool covers a distinct verification task, and the additional meta tools (pricing, find_data, request_data) are useful entry points without bloating the core purpose.
The server covers a comprehensive set of screening and validation tasks across sanctions, domain, email, phone, IBAN, and URL. It includes a discovery tool (find_data) and a suggestion tool (request_data) to fill gaps, though an IP checker or company registry lookup could be considered minor omissions.