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by io.github.whiteknightonhorse
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Global Temperature Anomaly

climate.indicators.temperature
Read-onlyIdempotent

Global surface temperature anomaly from NASA GISS — monthly readings since 1880. Values in °C vs 1951-1980 baseline. Returns last 10 years by default (adjustable 1-50). Source: NASA Goddard Institute for Space Studies.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "climate.indicators.temperature"
  }
}

Input Schema

NameRequiredDescriptionDefault
yearsNoNumber of years of data to return (1-50, default 10). Data is monthly.

Output Schema

NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds the default return range (10 years, adjustable 1-50) and source, which is useful but not extensive. No contradictions 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.

Conciseness5/5

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

Two sentences, no fluff, front-loaded with essential information. Every sentence is informative and necessary.

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 output schema exists, the description adequately covers source, data type, units, baseline, time range, and configurability. No missing context for effective use.

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?

The schema covers 100% of parameters, with the 'years' parameter description already including range and default. The description repeats this info but adds no new semantic depth beyond the 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 provides global surface temperature anomaly data from NASA GISS, specifying the baseline (1951-1980), unit (°C), time period (since 1880, monthly), and default range. It distinguishes itself from sibling climate indicators (e.g., CO2, methane) by being temperature-specific.

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 implies when to use (temperature anomaly queries) through specific content, but lacks explicit guidance on when not to use or alternative tools. However, the sibling context (other climate indicators) provides implicit differentiation.

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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