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Get Series

get_series
Read-onlyIdempotent

Fetch one or more Bank of England IADB series by code over a date range. Requires BoE series codes (e.g. IUDBEDR = Bank Rate, IUDSOIA = SONIA, XUDLUSS = USD/GBP, XUDLERS = EUR/GBP). Use list_known_series or the convenience tools (bank_rate, sonia, usd_gbp, eur_gbp) if you do not know the code. Returns parsed JSON: one entry per series with observations [{date, value}].

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd date "DD/Mon/YYYY", ISO "YYYY-MM-DD", or "now" (default "now").
fromYesStart date "DD/Mon/YYYY" (e.g. "01/Jan/2024") or ISO "YYYY-MM-DD".
series_codesYesBoE series codes, e.g. ["IUDBEDR","IUDSOIA"]. Also accepts a single comma-separated string.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "from": "2024-01-01",
      +    "series_codes": [
      +      "IUDBEDR"
      +    ]
      +  },
      +  {
      +    "from": "01/Jan/2024",
      +    "series_codes": [
      +      "IUDSOIA",
      +      "XUDLUSS"
      +    ],
      +    "to": "2024-12-31"
      +  }
      +]
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds return format details ('Returns parsed JSON: one entry per series with observations [{date, value}]') and context about the date range, going beyond the annotations.

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

Conciseness5/5

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

The description is three concise sentences: purpose, prerequisites/alternatives, and return format. Every sentence adds value with no redundancy, and it is front-loaded with the primary function.

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?

For a tool with no output schema, the description covers the return structure and prerequisites adequately. It lacks error handling details, but given the simple complexity, it is sufficiently complete.

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

Parameters4/5

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

Schema coverage is 100% with clear parameter descriptions, so the baseline is 3. The description adds concrete code-to-meaning mappings (e.g., IUDBEDR = Bank Rate) that enrich the semantic understanding beyond the schema.

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

Purpose5/5

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

The description clearly states it fetches BoE IADB series by code over a date range, with a specific verb and resource. It also differentiates from siblings by explicitly pointing to list_known_series and convenience tools (bank_rate, sonia, usd_gbp, eur_gbp).

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

Usage Guidelines5/5

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

It provides explicit usage guidance: requires BoE series codes and says to use alternative tools if the code is unknown. This clearly distinguishes when to use this tool vs. alternatives.

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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