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plot_forecast

Generate forecast figures per series, showing annual rate of change with confidence bands and residuals, so model forecasts can be reviewed series by series.

Instructions

FIGURE — The forecasts of the last estimated model in the format of FUF and art: on top the annual rate of change (%) of the last horizon observations and the horizon forecasts, +-1 sigma dashed (the LEVEL with +-2 sigma when the series is not in logs); below, ERR, the residuals of those observations with +-2 sigma. The numbers are forecast's.

One figure PER SERIES, as FUF draws one page per series, so that the forecast report can go series by series: series empty (default) returns one figure for each; a series' name, only that one; "all", every series in a single grid. path (optional) is a directory, or with one series a file. On a VEC: the levels and the 95 % band of forecast (drvarma's forecaster on the VEC in levels), with ERR the level innovations.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "plot_forecast"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
pathNo
seriesNo
horizonNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the figure contents (annual rate of change, +/-1 sigma dashed, ERR residuals with +/-2 sigma) and the one-figure-per-series default, but does not describe file-writing side effects for `path` or whether existing files are overwritten.

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 front-loaded with the key purpose ("FIGURE") and organized into plot contents, per-series behavior, path behavior, and VEC handling. It is somewhat verbose and jargon-dense, but the content is relevant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a plotting tool with no output schema and no annotations, the description covers the visual output and series selection well. It leaves out what the required `name` refers to and does not clarify file-writing behavior, which are important for correct invocation.

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 0%, so the description must compensate. It explains `series` (empty/default, a name, or "all"), `path` (directory or file with one series), and uses `horizon` in describing observations and forecasts, but the required `name` parameter is not explained at all.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: it produces figures of the forecasts from the last estimated model. The FUF/art format and per-series behavior are clear, though jargon-heavy and not explicitly differentiated from sibling tools like forecast or plot_impulse_response.

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?

Implies it should be used after estimation when a forecast figure is needed, and explains how the `series` parameter selects one, all, or each series. It does not explicitly say when to use this versus `forecast`, `forecast_uncertainty`, or other plot tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.