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joshua-bailey

eiu-mcp-server

eiu_get_data

Retrieve EIU economic forecasts and indicators by country and series codes. Use optional frequency and date range to filter data for specific periods.

Instructions

Fetch EIU forecast/indicator data by country and series codes.

Use eiu_browse or eiu_search first to find valid codes.

Args: geography_codes: ISO 2-char codes (e.g. ['US', 'BR', 'CN']) series_codes: EIU series codes (e.g. ['DGDP', 'DCPI']) frequency: 'Yearly', 'Quarterly', or 'Monthly' min_date: Start date YYYY-MM-DD (default: 5 years ago) max_date: End date YYYY-MM-DD (default: 5 years ahead)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_dateNo
min_dateNo
frequencyNoQuarterly
series_codesYes
geography_codesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden. It clearly implies a read-only fetch operation, states the prerequisite of finding valid codes first, and documents default date ranges and accepted frequency values. It could add error/rate-limit behavior, but the default date behavior and non-destructive nature are usefully conveyed.

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 compact and well-structured. The high-level purpose is front-loaded, the prerequisite is stated in a single sentence, and the Args block is clean and easy to scan. No sentence is wasted or redundant.

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

Completeness5/5

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

Given the tool has an output schema, return-value documentation is not needed. The description covers all five parameters, provides valid examples, explains the required discovery workflow, and states defaults. Everything an agent needs to invoke the tool correctly is present.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates. It explains every parameter: ISO 2-char geography codes with examples, EIU series codes with examples, allowed frequency values, and date format/defaults for min_date and max_date. This is far beyond the bare 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 uses a specific verb ('Fetch') and a specific resource ('EIU forecast/indicator data') with clear scope by country and series codes. This distinguishes it well from the sibling tools eiu_browse and eiu_search, which are for finding codes rather than retrieving data.

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 explicitly explains the intended workflow: use eiu_browse or eiu_search first to find valid codes, then call this tool. This is clear guidance on when to use this tool versus the alternatives, leaving no ambiguity for the agent.

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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