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El Tablero: Argentina economic data

Get a series' history

get_series
Read-onlyIdempotent

Return the historical values of one series with its metadata (name, unit, frequency, source, page URL, last date and value). Use it for past and current values; use get_projection for future ones. Needs a key from search_series; well-known keys: bcra:27 monthly inflation, bcra:28 annual inflation, bcra:4 retail USD rate, bcra:5 wholesale USD rate, bcra:1 reserves, bcra:7 BADLAR rate, bcra:44 TAMAR rate, bcra:31 UVA, bcra:30 CER. Without range or from it returns the last year for daily series and the last five years for the rest. At most 500 points, the most recent ones; a note says how many older points were left out. An unknown key returns an error that asks to search first. Read-only, no side effects, no authentication. Rate limited to 60 calls per minute per IP. Data updates at most once per business day.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesSeries key with its source prefix, as returned by search_series: "bcra:27", "datos:143.3_NO_PR_2004_A_31", "derivada:brecha_blue".
fromNoStart date as YYYY-MM or YYYY-MM-DD; rounded down to the first day of that month. Takes precedence over range.
rangeNoTime window ending at the last available value: 1m, 3m, 6m, 1y, 5y or max (full history). Ignored if from is given.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes
urlYes
nameYes
noteNo
unitYes
pointsYes[date YYYY-MM-DD, value], oldest first
sourceYes
categoryYes
frequencyYesD daily, M monthly, T quarterly, S semiannual, A annual
last_dateYes
last_valueYes
attributionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already establish read-only/idempotent/non-destructive, and the description goes well beyond them: default windows (1 year daily, 5 years otherwise), the 500-point cap with a truncation note, error behavior for unknown keys, 60 calls/min per IP rate limit, and once-per-business-day refresh cadence.

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?

Front-loaded with purpose, then routing, then defaults and limits - a logical order with no filler. It is dense but each clause carries distinct information (defaults, cap, error, rate limit), though the single long block is slightly heavy for a 3-parameter tool.

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?

Covers everything an agent needs before calling: required key provenance, default windows, result cap and truncation signaling, error semantics, rate limits, and auth requirements. With an output schema present, it correctly refrains from enumerating return fields in detail.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds value the schema lacks: the default behavior when neither from nor range is supplied, and concrete well-known key examples beyond the schema's sample values. It does not restate the from/range precedence rule that the schema already carries.

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 (return) and resource (historical values of one series) plus the metadata set returned. It explicitly distinguishes itself from get_projection ("use get_projection for future ones"), so an agent can route correctly without reading either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when-to-use (past/current values), when-to-use-the-alternative (future values -> get_projection), and a prerequisite (a key from search_series). It even supplies well-known keys, which is unusually actionable guidance.

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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