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	Default
`links`	No
`result`	Yes
`request`	Yes
`sources`	No
`success`	Yes
`version`	No
`freshness`	No
`timestamp`	Yes
`next_actions`	No

Schema Changelog

Changes observed during successful MCP inspections.

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

Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral context: exact conversion formulas, rejection of values below absolute zero, output fields, and a direct REST fallback. No contradiction 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.

Conciseness4/5

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

The description is longer than average but well-structured with labeled sections: use cases, exclusions, computation details, inputs, examples, outputs, formula, fallback, and docs. There is minor redundancy in repeating formulas, but most content earns its place.

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?

For a deterministic 3-parameter converter with full schema coverage, an output schema, and read-only annotations, the description supplies everything an agent needs: formulas, invalid-input rejection, complete JSON examples, fallback endpoint, and documentation link.

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 clearly. The description adds useful formula context and examples, but does not materially expand parameter meaning beyond the schema, so the baseline 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 opens with concrete use cases (weather, cooking, body, laboratory) and names the exact operation: converting between Celsius, Fahrenheit, Kelvin, and Rankine. This clearly distinguishes it from generic convert_units and other calculator siblings.

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?

It explicitly states when to use the tool, instructs the agent to call it directly rather than computing from memory, and gives clear do-not-use conditions for temperature differences and heat energy. The reference to an energy alternative satisfies the when-not/alternatives requirement.

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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