Validate a US ABA bank routing number (9 digits) by its checksum. Catch typos before initiating an ACH/wire payout. Pure-algorithm; nothing leaves the machine.
| Name | Required | Description | Default |
|---|---|---|---|
| routing_number | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that validation is algorithmic ('chechsum'), locally executed ('nothing leaves the machine'), and requires a 9-digit string. It could mention the return type or error handling, but for a simple validation, this is sufficient.
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: the first states purpose and method, the second adds usage context and safety guarantee. No redundant words, front-loaded with key information.
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 is simple (one parameter, deterministic). The description covers what, why, and safety. It doesn't explicitly state the return value, but that is often implicit for validation tools. Sibling tools provide context for differentiation. Slightly incomplete but adequate.
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 0% description coverage, but the description compensates by specifying the parameter is a US ABA routing number with a 9-digit format and checksum validation. This adds essential meaning beyond the schema's title.
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 verb 'Validate' and the resource 'US ABA bank routing number (9 digits)' with the method 'by its checksum'. It distinguishes from sibling tools like validate_iban or validate_eu_vat by specifying the US-specific routing number validation.
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?
It states the intended use case: 'Catch typos before initiating an ACH/wire payout'. While it doesn't explicitly mention when not to use it or alternatives, the sibling context and specificity imply its usage domain clearly.
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 type of validation or calculation (email domain, payout, reorder point, payment split, ABA routing, EORI, EU VAT, GTIN, IBAN, VAT rate). There is no overlap in purpose, and descriptions clarify the specific identifier or operation.
Most tool names use a verb_noun pattern (e.g., validate_aba_routing, check_email_domain), but some are noun phrases (payout_reconciliation, reorder_point, stripe_connect_split, vat_rate_by_country). While clearly descriptive, the verb-prefix inconsistency slightly reduces predictability.
With 10 tools, the server covers a focused set of commerce validation and calculation tasks without being too sparse or overwhelming. Each tool serves a clear, independent purpose.
The tool set covers key commerce validations (email, bank routing, IBAN, VAT, EORI, GTIN) plus useful calculations (payout, reorder, payment split, VAT rates). Minor gaps exist (e.g., phone/address/credit card validation, currency conversion), but the coverage is coherent for the stated domain.