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itu-mcp

itu-mcp

by yatuk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Archive: Exam Schedule

archive_exam_schedule
Read-onlyIdempotent

Retrieve a term's archived final exam schedule with date, time, place, and type; filter by branch or exact course code and check if coverage exists.

Instructions

Final exam schedule the archive recorded for a term (date, day, time, place, exam type), optionally filtered by branch or exact course code. Most terms have no recorded schedule: 'coverage' is then 'exam_schedule_not_recorded', which means the schedule was never captured, not that there are no exams. For the live current schedule use get_public_exam_schedule.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "term": "<term>"
    },
    "name": "archive_exam_schedule"
  }
}

Input Schema

NameRequiredDescriptionDefault
termYes
limitNo
branchNo
course_codeNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.1

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already carry the read-only/idempotent/non-destructive safety profile, so the bar is lower. The description adds genuinely useful behavior: most terms have no schedule and the 'coverage' field must be read as 'never captured', not 'no exams' — a nuance not derivable from annotations or schema.

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?

Three tightly packed sentences, purpose front-loaded, then the coverage caveat, then the alternative route. No filler and nothing that fails to earn its place.

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 shape need not be explained, and the key semantic trap about 'coverage' is pre-empted. The only gap is the unmentioned limit parameter, which is minor for a read-only filtered list.

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 coverage is 0%, so the description must compensate. It covers term (implied), branch, and course_code, and adds real meaning with 'exact course code' implying exact-match filtering, but it never mentions the limit parameter or its meaning, leaving one of four params undocumented.

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 resource ('final exam schedule the archive recorded for a term') with the fields returned (date, day, time, place, exam type), and explicitly distinguishes itself from the live sibling get_public_exam_schedule. An agent can select between the two without opening either schema.

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?

Names the alternative explicitly ('For the live current schedule use get_public_exam_schedule'), giving a clear when-to-use-this-vs-that rule. It also warns about the common 'exam_schedule_not_recorded' case, telling the agent what to expect and how to interpret it.

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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