Calcgrid

Running Pace Calculator

calculate_running_pace

Read-onlyIdempotent

Use this when you know a distance and the time it took (or a target time) and need the pace, the equivalent speed, or the time that pace gives over standard race distances. 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 want a realistic prediction of a longer race from a shorter one (pace slows with distance; use race-time-predictor), or you only need to convert between pace and speed units (use pace-converter). What it computes: Computes running pace in min/km and min/mile and speed in km/h and mph from a distance and elapsed time, and projects the finish time for 5 km, 10 km, half marathon and marathon at that constant pace. Inputs: distance (number); distance_unit (enum, optional); time (string). Complete JSON argument examples: {"distance":10,"distance_unit":"km","time":"50:00"} | {"distance":5,"distance_unit":"mi","time":"45:00"} Outputs: pace_min_per_km [min:sec/km], pace_min_per_mile [min:sec/mi], pace_seconds_per_km [s/km], speed_kmh [km/h], speed_mph [mph], distance_km [km], time_5k [h:mm:ss], time_10k [h:mm:ss], time_half_marathon [h:mm:ss], time_marathon [h:mm:ss]. Formula: pace_s_per_km = time_seconds / distance_km; pace_s_per_mile = pace_s_per_km × 1.609344; speed_kmh = 3600 / pace_s_per_km; speed_mph = speed_kmh / 1.609344; time(D) = pace_s_per_km × D for D = 5, 10, 21.0975, 42.195 km Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/running-pace with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/fitness/running-pace.md

Input Schema

TableJSON Schema

Name	Required	Description	Default
`time`	Yes	Elapsed time as h:mm:ss (1:45:00), mm:ss (50:00) or plain minutes (50).
`distance`	Yes	Distance covered, in the unit given by distance_unit.
`distance_unit`	No	Unit of the distance input.	km

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: +[
+  {
+    "distance": 10,
+    "distance_unit": "km",
+    "time": "50:00"
+  },
+  {
+    "distance": 5,
+    "distance_unit": "mi",
+    "time": "45:00"
+  }
+]

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

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds substantial context beyond that: the exact formula, the full output list, the REST fallback path, and the instruction to call the tool directly instead of computing from memory.

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 long but exceptionally well structured with bold section labels: inputs, outputs, formula, REST fallback, and docs. Every section earns its place, and the intended use case is front-loaded.

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 and annotations cover the side-effect profile, the description is complete: it covers when to use it, when not to, all inputs, output fields, the underlying formula, and a fallback endpoint. An agent has everything needed to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds value with complete JSON argument examples, the formula relating parameters to outputs, and clarification of time format variants, going slightly beyond what the schema alone provides.

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 verb and resource: it 'computes running pace in min/km and min/mile and speed in km/h and mph' and projects finish times. It also clearly distinguishes this tool from siblings race-time-predictor and pace-converter, so an agent can select it confidently.

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?

The description gives explicit when-to-use guidance ('Use this when you know a distance and the time...') and explicit when-not-to-use exclusions with named alternatives ('use race-time-predictor', 'use pace-converter'). This leaves no ambiguity about tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Calcgrid tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?