Calcgrid

Kinetic Energy Calculator

calculate_kinetic_energy

Read-onlyIdempotent

Use this when you need the energy of motion of an object of known mass and speed (vehicle, projectile, ball), for example to compare impact or braking energies. Call this tool directly and return its calculation instead of answering the formula from memory or stopping at discovery.

Do not use this when rotation contributes significantly (rotational energy ½·I·ω² is not included), speeds approach the speed of light (relativistic formula needed), or you need energy from height (use potential-energy). What it computes: Computes the translational kinetic energy of a moving mass from KE = ½·m·v², reported in joules, kilojoules, kilowatt-hours and kilocalories. Inputs: mass_kg (number, kg); velocity_m_s (number, m/s). Complete JSON argument examples: {"mass_kg":1200,"velocity_m_s":25} | {"mass_kg":0.145,"velocity_m_s":40} Outputs: kinetic_energy_j [J], kinetic_energy_kj [kJ], kinetic_energy_kwh [kWh], kinetic_energy_kcal [kcal], velocity_km_h [km/h]. Formula: KE = ½ × mass_kg × velocity_m_s²; kJ = J / 1000; kWh = J / 3,600,000; kcal = J / 4184 Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/kinetic-energy with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/physics/kinetic-energy.md

Input Schema

TableJSON Schema

Name	Required	Description	Default
`mass_kg`	Yes	Mass of the moving object in kilograms. Unit: kg.
`velocity_m_s`	Yes	Speed in metres per second (km/h ÷ 3.6, mph × 0.44704). Limited to 10 % of the speed of light, below which the classical formula is accurate to within 1 %. Unit: m/s.

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: +[
+  {
+    "mass_kg": 1200,
+    "velocity_m_s": 25
+  },
+  {
+    "mass_kg": 0.145,
+    "velocity_m_s": 40
+  }
+]

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

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already provide readOnlyHint=true, idempotentHint=true, destructiveHint=false, and the description adds meaningful behavioral context: it discloses the exact computation, the output units (J, kJ, kWh, kcal, km/h), and that rotational/relativistic effects are ignored. It also indicates the tool returns a calculation and should be used rather than the agent doing the math itself.

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?

The description is well organized with front-loaded usage guidance, followed by 'what it computes', inputs, outputs, formula, REST fallback, and docs. Each section is concise and adds a distinct type of information; there is no filler.

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 simplicity of a two-parameter pure calculation, the description covers all necessary aspects: when to use, exclusions, formula, units, examples, and output fields. With an output schema present, nothing needed to invoke the tool correctly is missing.

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 input schema already has full description coverage (100%) with units, examples, min/max constraints, and conversion hints. The description's parameter list and JSON examples largely restate the schema, adding little new parameter-level meaning beyond the formula context.

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 explicitly states a specific verb and resource: it 'computes translational kinetic energy' using KE = ½·m·v². It clearly differentiates from related physics calculations by listing exclusions (rotational motion, relativistic speeds, gravitational potential energy), which distinguishes it from sibling calculators even without naming one.

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?

Explicitly states when to use ('when you need the energy of motion of an object of known mass and speed...'), when not to use (rotation significant, near light speed, energy from height), and even names an alternative for height ('use potential-energy'). It also instructs the agent to call the tool directly instead of answering from memory.

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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