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DF Market Intelligence

DF Market Intelligence

by nasosal92
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

macro_series

Fetch up to 260 historical observations and summary statistics for a US macro series by FRED ID to analyze economic trends and support market research.

Instructions

Macro time series — History (up to ~260 observations) plus summary stats for one US macro series by FRED id. Costs $0.005 USDC per call (x402 on Base), paid automatically from your configured wallet.

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": {
      "id": "<id>"
    },
    "name": "macro_series"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesFRED series id, e.g. CPIAUCSL, UNRATE, DGS10

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does a good job disclosing the return content, observation limit, per-call cost, payment rail, and wallet behavior. It still does not state whether the operation is read-only, error behavior for invalid ids, or rate limits, but the key operational traits are disclosed.

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 two dense sentences with no wasted words. It front-loads what the tool returns before covering cost and payment mechanics.

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 simple one-parameter read-style series retrieval tool with no output schema, the description covers the essential return shape and cost context. More detail on the exact summary-stat fields or response format would make it fully complete, but an agent has enough to invoke it correctly.

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?

Schema description coverage is 100%, and the single parameter is fully documented in the schema with FRED id examples. The description only repeats 'by FRED id' and adds no further semantics beyond the schema, so the baseline of 3 is appropriate.

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 resource and scope: one US macro time series by FRED id, returning history (up to ~260 observations) plus summary stats. It is clear what the tool does, but it does not explicitly distinguish itself from siblings such as macro_latest or macro_calendar.

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 implied by the phrase 'History ... for one US macro series by FRED id,' suggesting it is for historical series retrieval. However, it gives no explicit when-to-use guidance, exclusions, or alternative tools for related macro queries.

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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