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achlens

achlens

by mscott9160-web
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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lookup_ach_code

Retrieve definitions for ACH return, NOC, transaction, SEC, or service-class codes to interpret parsed records and resolve what a code means.

Instructions

Look up a return, NOC, transaction, SEC, or service-class code.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "kind": "<kind>",
      "code": "<code>"
    },
    "name": "lookup_ach_code"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYes
kindYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full disclosure burden, and it says nothing about behavior: whether lookups are case-sensitive, what happens on an unknown code, whether the call is idempotent/read-only, or any rate limits. The presence of an output schema excuses it from explaining return values, but for a two-required-parameter tool with zero annotation coverage this is thin.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single short sentence with the verb front-loaded and no filler; nothing is wasted. It is arguably too terse given the unanswered `kind`/`code` semantics, but as a conciseness measure it is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple, read-only in nature, and has an output schema, so return-value detail is not required. What is missing for correct invocation is any definition of the `kind` values and the `code` format, which neither the schema nor the annotations supply.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and there are no enums, so the description must compensate. It partially does by enumerating the five kind categories (return, NOC, transaction, SEC, service-class), which effectively hints at valid values for the `kind` parameter, but the `code` parameter's expected format (e.g., R01, a three-character code) is entirely undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb ("Look up") and resource (an ACH code) and enumerates the five code categories the tool covers: return, NOC, transaction, SEC, and service-class. That is enough to distinguish it from file-oriented siblings like parse_ach_file or validate_ach_file, though it never names an alternative explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no prerequisites, and no mention of sibling tools such as check_routing_number (the other single-code lookup). The agent is left to infer that this is the right tool for decoding a code value.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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