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fred-mcp

by mcpwright

Get a data point's revision history

get_revision_history
Read-only

Retrieve the revision history of a FRED data point, showing the initial value, each revision with publication date, current value, and total drift.

Instructions

One data point's life across revisions: earliest archived print -> today.

`series_id`: a FRED series ID. `observation_date`: the data point's PERIOD
START date (ISO) — quarterly series use quarter starts (Q4 2008 =
"2008-10-01"), monthly use month starts. Returns the earliest archived
value, every revision with its publication date, the current value, and
the total drift.

Caveat: ALFRED's archive starts late for many series (`archive_starts`
shows where). `initial_value` is the true first print — what
decision-makers actually saw — only when the archive reaches back to the
observation's original release.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
series_idYes
observation_dateYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
series_idYesThe FRED series ID
titleYesSeries title
observation_dateYesThe observation the history is for (period start date)
unitsYesUnits of the values
archive_startsNoThe first vintage in ALFRED's archive for this point. If this is much later than observation_date, initial_value is the earliest ARCHIVED value, not the true first print
initial_valueYesThe value in ALFRED's earliest archived vintage — the as-published 'real-time' number when archive_starts reaches back to the observation's release
current_valueYesThe value as published today, after all revisions
total_revisionNocurrent_value - initial_value (null if either is missing)
stepsYesEach distinct value the point has held, oldest first (consecutive re-publications of an unchanged value are merged)
steps_truncatedNoTrue if middle revisions were omitted to cap the list (the initial and current steps are always kept)
Behavior4/5

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

Annotations provide readOnlyHint and openWorldHint, but the description adds critical behavioral context: it details the return value (initial, revisions, current, drift), explains archive start caveats, and clarifies what 'initial_value' represents. No contradiction with annotations.

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

Conciseness4/5

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

The description is well-structured with an overview sentence, parameter explanations, and a caveat paragraph. It is concise without unnecessary words, though the caveat could be slightly more streamlined.

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 tool's complexity (revision history with archive limitations) and the presence of an output schema, the description adequately covers input, output, and important caveats. It is complete for an agent to understand usage.

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 has 0% description coverage, but the description fully explains both parameters: series_id is a FRED series ID, observation_date is the period start date in ISO format with examples for quarterly and monthly series. This adds significant 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 'one data point's life across revisions' and specifies the output includes earliest archived value, every revision with publication date, current value, and total drift. It distinguishes itself from siblings like get_latest or get_observations by focusing on revision history.

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 use for revision history but does not explicitly state when to use this tool vs alternatives like compare_series or get_observations. No exclusions or when-not-to-use guidance is provided.

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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