UETGPT

Calculate UET Taxila merit aggregate

calculate_merit_aggregate

Read-onlyIdempotent

Use this when a user gives their SSC (matric), HSSC Part-I (FSc first year) and entry test (ECAT/TCAT) marks and wants their UET Taxila merit aggregate, eligibility, or which programs they might get. Applies the official 17% SSC + 50% HSSC Part-I + 33% entry test formula. Ask for any missing marks; never guess them. BS Mathematics and BS Physics have no entry test and use 30% SSC + 70% HSSC Part-I (basicSciencesAggregate); for those alone, pass 0 entry test marks if the user took no test. Do not use it for other universities' formulas.

Input Schema

TableJSON Schema

Name	Required	Description
`sscMarks`	Yes	SSC (matric) marks obtained.
`sscTotal`	No	SSC total marks, usually 1100 (1200 on some boards).
`hsscMarks`	Yes	HSSC Part-I (FSc first year) marks obtained.
`hsscTotal`	No	HSSC Part-I total marks, usually 550.
`hafizOrNcc`	No	True only if the user says they are Hafiz-e-Quran or hold an NCC certificate (+20 HSSC marks for merit only, not for eligibility).
`entryTestMarks`	Yes	Entry test (ECAT or TCAT) marks obtained.
`entryTestTotal`	No	Entry test total marks, 400 for ECAT.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`note`	Yes
`formula`	Yes
`aggregate`	Yes
`meritNote`	Yes
`components`	Yes
`hsscPercent`	Yes
`comparedAgainst`	Yes
`formulaSourceUrl`	Yes
`hafizBonusApplied`	Yes
`basicSciencesFormula`	Yes
`basicSciencesAggregate`	Yes
`eligibleForEngineering`	Yes
`eligibleForCsMathPhysics`	Yes
`programsAtOrBelowLatestClosingMerit`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedOct 4, 2026

addedOutput schema / properties / basicSciencesAggregate
```
Added value: +{
+  "type": "number"
+}
```
addedOutput schema / properties / basicSciencesFormula
```
Added value: +{
+  "type": "string"
+}
```

changedOutput schema / required

Previous value: -[
-  "aggregate",
-  "components",
-  "hsscPercent",
-  "hafizBonusApplied",
-  "eligibleForEngineering",
-  "eligibleForCsMathPhysics",
-  "programsAtOrBelowLatestClosingMerit",
-  "comparedAgainst",
-  "formula",
-  "formulaSourceUrl",
-  "meritNote",
-  "note"
-]New value: +[
+  "aggregate",
+  "basicSciencesAggregate",
+  "components",
+  "hsscPercent",
+  "hafizBonusApplied",
+  "eligibleForEngineering",
+  "eligibleForCsMathPhysics",
+  "programsAtOrBelowLatestClosingMerit",
+  "comparedAgainst",
+  "formula",
+  "basicSciencesFormula",
+  "formulaSourceUrl",
+  "meritNote",
+  "note"
+]

First observedOct 2, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered; the description goes further by disclosing the exact scoring formula, the basic-sciences exception formula, and the instruction to pass 0 entry-test marks for that case. It does not discuss rounding, output shape, or failure modes (e.g., marks exceeding totals), which keeps it from a 5.

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?

Four sentences, front-loaded with the trigger condition and the formula, then edge cases and the exclusion. Every sentence carries information, though the run-on first sentence packs three separate intents and could be split.

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?

An output schema exists, so return values need not be explained, and the description covers the remaining gaps an agent would face: the two different formulas, the program-specific branch, and the missing-input policy. Nothing needed to invoke it correctly is absent.

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, but the description adds real meaning: it tells the agent that entryTestMarks may legitimately be 0 for basic-sciences programs and that missing marks must be requested rather than defaulted. Those are semantic additions the schema's per-field descriptions do not convey.

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+resource (calculate UET Taxila merit aggregate) and immediately names the concrete artifacts it produces: merit aggregate, eligibility, and program prospects. It also distinguishes itself from siblings like estimate_uet_fees and list_uet_programs by naming a different domain (admissions merit math).

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?

Gives explicit when-to-use ('when a user gives their SSC, HSSC Part-I and entry test marks'), an explicit when-not ('Do not use it for other universities' formulas'), and an alternate branch condition for BS Mathematics/BS Physics that uses a different formula. The 'ask for missing marks; never guess' rule is an actionable operating instruction.

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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