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US Economic Data (FRED)

fred_series

Any FRED economic time series by id or alias: CPI, core PCE, unemployment, payrolls, GDP, fed funds, SOFR, Treasury yields, mortgage rates, M2, oil, VIX, jobless claims... Latest value, change, 1-year % change and history. Use for macro analysis and economic questions.

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": {
      "series": "<series>"
    },
    "name": "fred_series"
  }
}

Input Schema

NameRequiredDescriptionDefault
endNo
limitNo
startNo
seriesYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It helpfully discloses that results include the latest value, change, 1-year percent change, and history, but it does not discuss rate limits, authentication, error behavior, or how start/end/limit affect the returned history.

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 front-loaded: it states the core capability first, then supported indicators, then returned fields, then usage context. The example list is long but directly useful for alias discovery, so every part earns its place.

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

Completeness2/5

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

The tool is a simple read operation and has an output schema, so return values need less explanation. However, the input schema has 0% description coverage and the description only clarifies the `series` parameter, leaving `start`, `end`, and `limit` undocumented and making historical queries harder to construct correctly.

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 for parameter ambiguity. It does well for the required `series` parameter by explaining that FRED ids or aliases are accepted and giving many examples, but it says nothing about the `start`, `end`, or `limit` parameters.

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 clearly identifies the resource as any FRED economic time series, retrievable by id or alias, and gives concrete examples of supported indicators. It is specific enough to distinguish this from generic economic tools, though it does not explicitly differentiate itself from overlapping siblings such as us_treasury_yields or central_bank_rates.

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?

It states a clear usage context: 'Use for macro analysis and economic questions.' It does not provide exclusions or explicitly route the agent away from overlapping tools, but the intended use case is clear.

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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