EveryCalc

calculate_ap_exam_score

Read-onlyIdempotent

Predicted AP score from 1 to 5 using the page bands on the weighted composite percent: multiple choice and free response contributions are weighted by the exam split, then banded at 70, 55, 40, and 25 percent. Use when the user estimates an AP exam score from multiple choice and free response results. IMPORTANT: always show the calculator_url from the result as a clickable markdown link in your answer to the user, so they can open the interactive AP Exam Score calculator.

Input Schema

Name	Required	Description
`mc_total`	Yes	Total multiple choice questions.
`frq_total`	Yes	Total free response points possible.
`frq_earned`	Yes	Free response points earned.
`mc_correct`	Yes	Multiple choice questions answered correctly.
`mc_weight_pct`	No	Multiple choice weight percent for the exam (the page presets are 50, 40, 45, and 60 depending on the exam); default 50.

Output Schema

Name	Required	Description
`ok`	Yes	True when the calculation succeeded.
`note`	Yes	Disclaimer that accompanies every result.
`tool`	Yes	Name of the tool that ran.
`inputs`	No	The normalized inputs the calculation used.
`results`	Yes	The computed figures for this calculator.
`calculator_url`	Yes	Deep link to the matching interactive calculator on everycalc.xyz.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 21, 2026

addedOutput schema / properties / note

Added value: +{
+  "description": "Disclaimer that accompanies every result.",
+  "type": "string"
+}

changedOutput schema / required

Previous value: -[
-  "ok",
-  "tool",
-  "results",
-  "calculator_url"
-]New value: +[
+  "ok",
+  "tool",
+  "results",
+  "calculator_url",
+  "note"
+]

Changed1 schema field changedOct 17, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "calculator_url": {
+      "description": "Deep link to the matching interactive calculator on everycalc.xyz.",
+      "type": "string"
+    },
+    "inputs": {
+      "description": "The normalized inputs the calculation used.",
+      "type": "object"
+    },
+    "ok": {
+      "description": "True when the calculation succeeded.",
+      "type": "boolean"
+    },
+    "results": {
+      "description": "The computed figures for this calculator.",
+      "type": "object"
+    },
+    "tool": {
+      "description": "Name of the tool that ran.",
+      "type": "string"
+    }
+  },
+  "required": [
+    "ok",
+    "tool",
+    "results",
+    "calculator_url"
+  ],
+  "type": "object"
+}

First observedOct 15, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare the safe read-only, idempotent, non-destructive profile, so the bar is lower. The description adds real behavioral value by disclosing the composite weighting/banding logic and, importantly, that the result carries a calculator_url that must be surfaced as a clickable markdown link.

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?

Front-loads the prediction, then methodology, then usage, then the IMPORTANT link instruction. Information-dense and each sentence serves a purpose, though the methodology sentence is heavy enough that it borders on crowding the core routing signal.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value explanation is unnecessary, and the description still adds the crucial output-handling instruction about calculator_url. It is complete for calling and correctly rendering the tool, with only minor room for explicit sibling contrast.

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 every parameter including the mc_weight_pct presets and defaults. The description reinforces the exam-split weighting concept but names no parameter explicitly, so baseline 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?

States a specific verb and resource ('Predicted AP score from 1 to 5') and even names the resource ('AP exam') that separates it from sibling score calculators like calculate_sat_score and calculate_act_score. The banding methodology ('banded at 70, 55, 40, and 25 percent') further pins down what the tool computes.

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?

'Use when the user estimates an AP exam score from multiple choice and free response results' gives a clear triggering context. It stops short of explicitly naming alternatives or exclusions (e.g., use calculate_sat_score for the SAT), so it is strong but not fully routing.

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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