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FRED Series

get_fred_data
Read-only

One series from Oxford Ledge's macro SNAPSHOT (about 41 FRED / Treasury series, newest observation each) by FRED id. Returns {series, data: {series, name, value, date, ytdChange, _source}, observation: 'latest_only', note} -- ONE observation, never a history. A series outside the snapshot returns {series, error, available}. THIRD-PARTY LICENSED SERIES ARE REFUSED WITH THE REASON (2026-09-13): the ICE BofA OAS credit spreads (BAMLH0A0HYM2, BAMLC0A0CM, BAMLC0A1CAAA, BAMLH0A1HYBB, BAMLH0A2HYB, BAMLH0A3HYC), VIXCLS and UMCSENT are licensed content FRED redistributes under its own terms and Oxford Ledge does not; the answer is {series, data: null, refusal_reason: 'third_party_licence', licensor, error, note, directional, directional_unavailable_reason}. RESTRICTED posture: a keyed tool on the hosted channel. Caveats ride the response's tool_notes. Needs an Oxford Ledge API key that the client's operator configures; anonymous callers are refused.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seriesYesFRED series ID (e.g. GDP, UNRATE, CPIAUCSL, DFF)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true. The description goes far beyond by disclosing the exact response shape, the latest-only observation constraint, refusal behavior for third-party licensed series (with a list of affected IDs and reason codes), the RESTRICTED/keyed posture, the need for an operator-configured API key, and that caveats appear in tool_notes. This is rich behavioral context that annotations do not cover.

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

Conciseness3/5

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

Front-loads the core purpose and return shape effectively, but the middle section is dense with error/refusal detail, a long enumerated ID list, and parenthetical date notes that reduce scannability. The information is valuable but could be structured more cleanly.

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?

For a single-parameter, keyed, read-only tool with no output schema, the description covers the return format, the latest-only constraint, refusal cases with reason fields, auth requirements, and where caveats live. An agent has everything needed to call it correctly and interpret responses.

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 schema example (GDP, UNRATE) plus the description's enumeration of specific FRED IDs (BAMLH0A0HYM2, VIXCLS, etc.) illustrate valid and invalid inputs. Baseline 3 is appropriate since the schema already documents the single parameter fully.

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?

States a specific verb+resource (retrieve one FRED series from Oxford Ledge's macro snapshot), keyed by FRED id, and explicitly scopes that only the newest observation is returned, not history. This distinguishes it clearly from siblings like get_yield_curve or get_economic_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?

The description implies usage by specifying 'newest observation each' and 'one series from the snapshot,' which implies when this tool is appropriate (single-series latest value) versus a history tool. However, it never explicitly names alternatives or states when NOT to use this tool, leaving the agent to infer limits.

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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