Hopi

UCAS points calculator

hopi_ucas_points_calculator

Read-onlyIdempotent

Add up UCAS tariff points from A-level grades using the current tariff: A* 56, A 48, B 40, C 32, D 24, E 16. Give the number of grades at each level. Returns the total points and the number of grades counted. Source: https://hopi.co.uk/ucas-points-calculator/

Input Schema

TableJSON Schema

Name	Required	Description
`a`	No	Number of A grades (0 to 20)
`b`	No	Number of B grades (0 to 20)
`c`	No	Number of C grades (0 to 20)
`d`	No	Number of D grades (0 to 20)
`e`	No	Number of E grades (0 to 20)
`aStar`	No	Number of A* grades (0 to 20)

Output Schema

TableJSON Schema

Name	Required	Description
`summary`	Yes
`source_url`	Yes	The tool's page on hopi.co.uk (cite or open to check the figure)
`totalPoints`	Yes
`gradesCounted`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 20, 2026

addedOutput schema / required

Added value: +[
+  "gradesCounted",
+  "source_url",
+  "summary",
+  "totalPoints"
+]

First observedSep 20, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already mark the tool as readOnly, idempotent, and non-destructive. The description adds useful behavioral detail beyond those hints: the current tariff values, the input format, and the fact that it returns both the total points and the number of grades counted. This is sufficient for a simple calculator.

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 two efficient sentences plus a source URL. It front-loads the purpose and tariff, immediately gives the input convention, and then states the return values with no filler or repetition.

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?

The definition is complete for this tool: annotations cover safety and determinism, the schema covers all six parameters, an output schema exists, and the description explains the calculation rule, expected inputs, and return summary. An agent has everything needed to call it correctly.

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%, with each grade-count parameter already described and range-limited. The description adds the overall instruction to provide counts per level, but it does not materially extend what the schema already conveys, 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 ('Add up UCAS tariff points from A-level grades') and a clear resource domain, with the exact tariff values. It distinguishes itself from the large sibling set by focusing on A-level grades and the UCAS tariff, leaving no ambiguity about 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?

The description clearly instructs the user to 'Give the number of grades at each level,' which is exactly the input convention required. It does not explicitly name alternatives or exclusions, but none of the sibling tools serve the same UCAS-points purpose, so the context is strong enough for correct selection.

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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