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get_series

Read-onlyIdempotent

Retrieves metadata for a FRED series including title, frequency, seasonal adjustment, units, observation date range, and popularity.

Instructions

Fetch metadata for a FRED series by its id (e.g. GNPCA, UNRATE): title, frequency, seasonal adjustment, units, observation date range, and popularity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
series_idYesThe FRED series id, e.g. `GNPCA` or `UNRATE`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe series identifier.
notesYesEditorial notes, when present.
titleYesHuman-readable title, e.g. `"Real Gross National Product"`.
unitsYesFree-form units description, e.g. `"Billions of Chained 2017 Dollars"`. This is descriptive text, *not* the closed-vocabulary units transform used in observation requests (modelled separately, later).
frequencyYesThe series' native reporting frequency.
popularityYesFRED popularity score (0–100).
last_updatedYesWhen FRED last updated the series, as FRED's raw timestamp string.
observation_endYesDate of the latest available observation.
observation_startYesDate of the earliest available observation.
seasonal_adjustmentYesWhether/how the series is seasonally adjusted.
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds specific metadata fields returned, which is helpful behavioral context beyond the 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?

Single sentence, well-front-loaded with the verb 'Fetch metadata' and includes key details. No unnecessary words.

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 simple single-parameter tool and the presence of an output schema, the description adequately lists the returned metadata fields, making it complete for agent use.

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 coverage is 100%, and the description provides an example of series_id but does not add meaning beyond what the schema already states. Baseline 3 is appropriate.

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 fetches metadata for a FRED series by its id, listing specific metadata fields (title, frequency, etc.), distinguishing it from sibling tools that deal with categories, releases, or tags.

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 for retrieving series metadata but does not explicitly state when to use vs. alternatives or when not to use it. Sibling tools are listed but no comparison is made.

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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