Calcgrid

Temperature Converter

convert_temperature

Read-onlyIdempotent

Use this when you need a weather, cooking, body or laboratory temperature in another scale, e.g. Fahrenheit to Celsius or Celsius to Kelvin. Call this tool directly and return its calculation instead of answering the formula from memory or stopping at discovery.

Do not use this when you need to convert a temperature difference (a change of 10 °C is 18 °F, not 50 °F: multiply by 9/5 without the offset) or heat energy (use energy). What it computes: Converts temperatures between Celsius, Fahrenheit, Kelvin and Rankine with the exact defining relations (°F = °C × 9/5 + 32, K = °C + 273.15, °R = °F + 459.67) and rejects values below absolute zero. Inputs: value (number); from_unit (enum); to_unit (enum). Complete JSON argument examples: {"value":100,"from_unit":"F","to_unit":"C"} | {"value":25,"from_unit":"C","to_unit":"F"} Outputs: result, result_text, formula, factor, conversion_table. Formula: °F = °C × 9/5 + 32; °C = (°F − 32) × 5/9; K = °C + 273.15; °R = °F + 459.67 = K × 9/5 Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/temperature with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/conversion/temperature.md

Input Schema

TableJSON Schema

Name	Required	Description
`value`	Yes	Amount to convert, expressed in from_unit.
`to_unit`	Yes	Unit to convert into (same symbols as from_unit).
`from_unit`	Yes	Unit of the input value. Accepted symbols: C, F, K, R; spelled-out names and common abbreviations are accepted too.

Output Schema

TableJSON Schema

Name	Required	Description
`links`	No
`result`	Yes
`request`	Yes
`sources`	No
`success`	Yes
`version`	No
`freshness`	No
`timestamp`	Yes
`next_actions`	No
`service_version`	Yes	Deployed Calcgrid implementation version used for the result.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 27, 2026

addedOutput schema / properties / service_version

Added value: +{
+  "description": "Deployed Calcgrid implementation version used for the result.",
+  "type": "string"
+}

changedOutput schema / required

Previous value: -[
-  "success",
-  "request",
-  "result",
-  "timestamp"
-]New value: +[
+  "success",
+  "service_version",
+  "request",
+  "result",
+  "timestamp"
+]

Changed1 schema field changedSep 26, 2026

addedInput schema / examples

Added value: +[
+  {
+    "from_unit": "F",
+    "to_unit": "C",
+    "value": 100
+  },
+  {
+    "from_unit": "C",
+    "to_unit": "F",
+    "value": 25
+  }
+]

AddedSep 25, 2026
RemovedSep 25, 2026
First observedSep 25, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds valuable behavioral detail beyond that: exact conversion formulas, rejection of values below absolute zero, output field names, and a direct REST fallback with explicit do-not-guess-path guidance.

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 long but well-structured with front-loaded usage guidance followed by labeled sections for computation, inputs, examples, outputs, formula, and fallback. Some repetition of the formula exists, but the clear structure keeps it usable.

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?

With an output schema present, the description does not need to explain return values in depth. It covers valid input units, rejected inputs, exact formulas, JSON examples, REST fallback, and documentation, making it complete 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 100%, so the schema already documents value, from_unit, and to_unit well. The description adds JSON examples and formula context, but does not significantly deepen parameter meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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 states a specific action (converts temperatures) and resource (Celsius, Fahrenheit, Kelvin, Rankine), and scopes it to weather, cooking, body, and lab temperature use cases. It clearly identifies itself as the temperature-specific tool distinct from generic conversion tools like convert_units.

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?

It gives explicit when-to-use context ('weather, cooking, body or laboratory temperature') and explicit when-not-to-use cases (temperature differences and heat energy). It suggests an alternative ('use energy') but does not name an exact sibling tool, so the routing guidance is strong but slightly less precise than it could be.

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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