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Russia–NATO risk ladder

Forecast history

get_forecast_history
Read-onlyIdempotent

Published Metaculus probabilities by 2035 for an attack on European NATO or a seizure of Baltic territory, with the annual conversion for each observation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoYYYY-MM-DD
fromNoYYYY-MM-DD
langNoLanguage of text fields (default en)
seriesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered and the description's burden is lower. It adds domain context (published Metaculus probabilities, one annual conversion per observation), but says nothing about default time window, pagination, or what happens when from/to are omitted.

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?

One dense sentence with no wasted words, and the subject (what the data is) is front-loaded. It is slightly compressed — 'annual conversion for each observation' requires interpretation — but not padded.

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?

With no output schema, the description carries the burden of describing the return shape, and 'annual conversion for each observation' only partially does that. For a parameterized time-series retrieval tool, an agent still lacks guidance on default ranges and result granularity.

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 75%, so the schema already documents most parameters. The description implicitly maps to `series` (the two named threats) and to the 2035 endpoint, but adds nothing about the `to`/`from` format, defaults, or the `lang` parameter, so it does not compensate for the remaining coverage gap.

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?

The description names a concrete source (Metaculus), the two forecast targets ('attack on European NATO', 'seizure of Baltic territory' — matching the two enum values of `series`), and the 2035 horizon, so the resource is identifiable. It does not, however, distinguish this from the sibling `get_other_forecasts`, which is what would push it to a 5.

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

Usage Guidelines2/5

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

There is no explicit when-to-use guidance and no alternative is named, even though `get_other_forecasts` sits right next to it in the toolkit. Usage can only be inferred from the subject matter, so the agent gets no help routing between the two forecast tools.

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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