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mcpwright

fred-mcp

by mcpwright

Get observations

get_observations
Read-only

Get current post-revision observations for a FRED series within a date window, with optional transformations or frequency aggregation.

Instructions

A series' values in a date window, optionally transformed/downsampled.

`series_id`: a FRED series ID. `start`/`end`: ISO dates bounding the
window. `transform`: level | change | pct_change | pct_change_yoy | log.
`frequency`: optionally downsample to daily/weekly/monthly/quarterly/
semiannual/annual (with `aggregation` avg | sum | eop); only coarser than
the native frequency is valid. `max_points` caps the result, keeping the
most RECENT points (`truncated` tells you when the cap bit).

Values are CURRENT (post-revision) data. For numbers as originally
published, use `get_series_as_of` / `get_revision_history`.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
series_idYes
startNo
endNo
transformNolevel
frequencyNo
aggregationNoavg
max_pointsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
series_idYesThe FRED series ID
titleYesSeries title
unitsYesUnits of the VALUES RETURNED — the native units when transform='level', otherwise the transform (e.g. '% change from year ago')
transformYesThe transform applied (level if none)
frequencyYesFrequency of the values returned
observationsYesThe data points, oldest first
truncatedYesTrue if more observations exist than were returned — narrow the date range or raise max_points for more
Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint, but the description adds critical behavioral context: values are current post-revision data, and max_points truncation keeps most recent points with a truncated flag. This goes beyond 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 efficiently structured with a one-sentence summary followed by a bullet-like list of parameter details. Every sentence adds value without redundancy, and the most important info is front-loaded.

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 7 parameters, 1 required, and an output schema present (not shown), the description covers all parameter semantics, usage guidelines, and behavioral traits. It is fully self-contained and useful for an agent to select and invoke the tool.

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

Parameters5/5

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 explains each parameter: series_id (FRED series ID), start/end (ISO dates), transform (with options), frequency/aggregation (downsampling rules), and max_points (capping behavior). This adds full meaning beyond the bare schema.

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 returns 'A series' values in a date window, optionally transformed/downsampled', using specific verbs and resources. It distinguishes from siblings like get_revision_history and get_series_as_of by highlighting the transformation and downsampling capabilities.

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 provides explicit guidance on when to use alternatives, e.g., 'For numbers as originally published, use get_series_as_of / get_revision_history'. It explains transform and frequency options but does not explicitly state when not to use this tool.

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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