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prithvi1029

fred-economic-intelligence-mcp

by prithvi1029

compare_series

Retrieve and compare economic data from multiple FRED series simultaneously, fetching their metadata and observations in parallel.

Instructions

Retrieve and compare multiple FRED economic series.

This tool fetches metadata and observations for each requested
series concurrently.

Example series IDs:
["GDP", "UNRATE", "CPIAUCSL", "FEDFUNDS"]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
series_idsYes
observation_endNo
observation_startNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses concurrent fetching, which is a behavioral trait beyond the schema. However, it lacks details on rate limits, authentication needs, error handling, or idempotency. This is adequate but not rich for a tool with no 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 highly concise with three sentences: first states purpose, second adds concurrency detail, third provides example. It is front-loaded and efficient, with no wasted words.

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?

Given the tool has 4 parameters and an output schema exists, the description does not need to cover return values. However, it partially explains the 'series_ids' parameter via example but omits others. The core purpose is clear, but param details are inadequate, making it average in completeness.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It provides example series IDs, giving context for the 'series_ids' parameter, but does not explain 'limit', 'observation_start', or 'observation_end'. The example helps but leaves most parameters undefined, which is insufficient given the lack of schema descriptions.

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 the tool retrieves and compares multiple FRED economic series, specifying the verb ('Retrieve and compare') and resource ('multiple FRED economic series'). It also mentions concurrent fetching of metadata and observations, which differentiates it from sibling tools like get_series_metadata and get_series_observations that likely handle single series.

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

Usage Guidelines4/5

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

The description implies this tool is for comparing multiple series by fetching metadata and observations concurrently. While it does not explicitly state when not to use it or mention alternatives, the sibling context (e.g., get_series_metadata, get_series_observations) provides differentiation. A clearer exclusion or alternative mention would improve this dimension.

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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