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Boe Uk

by io.github.pipeworx-io
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Bank Rate

bank_rate
Read-onlyIdempotent

The Bank of England's official Bank Rate: the current rate, the date it took effect, the previous rate and when that one took effect, plus recent decision history (series IUDBEDR) — not just a raw observations list to infer a decision date from. Also returns the last N daily observations.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "last": 10
    },
    "name": "bank_rate"
  }
}

Input Schema

NameRequiredDescriptionDefault
lastNoNumber of most-recent observations (default 10).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "last": 10
+  }
+]
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, open-world, non-destructive, so the safety profile is covered. The description adds real behavioral value by enumerating exactly what data comes back (current rate, effective date, previous rate, prior effective date, decision history, plus last N daily observations) – important because there is no output schema.

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 front-loaded sentence that leads with the primary return value and then lists the supplementary ones, with zero filler. The em-dash aside is slightly dense but every phrase carries information.

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

Completeness4/5

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

Given one optional parameter, annotations covering safety, and no output schema, the description does the heavy lifting by describing return contents in detail. Minor gaps remain: no mention of units (percent), formatting of decision history, or maximum value for 'last', but nothing critical to correct invocation is missing.

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?

There is a single parameter with 100% schema description coverage ('Number of most-recent observations (default 10)'). The description's 'last N daily observations' merely restates the schema rather than adding format, limits, or units, so the baseline of 3 applies.

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 states a specific verb+resource: it returns the Bank of England's official Bank Rate along with the effective date, previous rate, and recent decision history (series IUDBEDR). It distinguishes itself from a raw observations list, implicitly contrasting with a sibling like get_series, though it never names the alternative tool directly.

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

Usage Guidelines3/5

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

Usage is only implied via the clause 'not just a raw observations list to infer a decision date from' – an agent can infer this tool is preferable when decision dates matter. There is no explicit when-to-use/when-not guidance and no named alternative among the many siblings.

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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