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itu-mcp

itu-mcp

by yatuk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Archive: Course Unlocks

archive_course_unlocks
Read-onlyIdempotent

Find which archived courses list a given course as a direct prerequisite. Use this reverse index for immediate unlocks, then check each course's eligibility rules for the real requirement.

Instructions

Which courses list the given course as a prerequisite, from the archive's reverse prerequisite index. This is the direct next level only, not the whole chain. Prerequisite rules have AND/OR alternatives and minimum grades that this flat list does not express, so passing the course does not by itself make the listed courses takeable: call explain_course_eligibility on a listed course for the real rule. 'coverage' is 'not_listed_as_prerequisite' when no course names it.

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": {
      "course_code": "<course_code>"
    },
    "name": "archive_course_unlocks"
  }
}

Input Schema

NameRequiredDescriptionDefault
course_codeYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.1

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive), so the bar is lower, yet the description still adds real behavioral context: that prerequisite rules contain AND/OR alternatives and minimum grades this flat list cannot express, and that a 'not_listed_as_prerequisite' coverage value signals an empty result. That is meaningful interpretation guidance beyond the structured fields.

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 core lookup semantics are front-loaded in the first sentence, followed by the scope limit and the misreading warning, each in its own sentence with no filler. Nothing could be removed without losing decision-relevant information.

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 values need not be re-described, and the description still usefully explains the meaning of the coverage field. The only gap is the undocumented input format for course_code, which for a single-identifier lookup tool is a minor omission.

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

Parameters2/5

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

There is one required parameter with 0% schema description coverage, so the description carries the full burden of documenting it, and it does not: no format, identifier style, or example for course_code is given. It only refers obliquely to 'the given course', adding nothing beyond what the schema name implies.

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 operation (reverse prerequisite lookup) on a specific resource and explicitly names the direction ('courses that list the given course as a prerequisite'), which separates it from the forward-looking prerequisite siblings. It also scopes the result set ('direct next level only, not the whole chain'), so an agent knows exactly what it will get back.

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?

It tells the agent when the output is insufficient ('passing the course does not by itself make the listed courses takeable') and routes to a named alternative ('call explain_course_eligibility on a listed course for the real rule'). The scope exclusion against the full chain is stated outright rather than left to inference.

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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