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Glama

list_enrolled_courses

Retrieve every KodeKloud course a learner is enrolled in, including title, category, difficulty, and progress status (In Progress, Completed, Not Started).

Instructions

List all courses the user is currently enrolled in on KodeKloud.

Returns titles, categories (Kubernetes, Cloud, Linux, IaC), difficulty levels, and current enrollment status (In Progress, Completed, Not Started).

Returns: EnrolledCoursesResponse containing the list of enrolled courses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesTotal count of enrolled courses.
errorNoError message if the operation or upstream request failed.
coursesNoList of enrolled courses.
warningNoDiagnostic warning or configuration guidance message.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; 'List' implies a safe read, and it discloses the shape of what comes back (titles, categories, difficulty, enrollment status). It says nothing about authentication scope, pagination, or ordering, which are the remaining behavioral gaps for a list operation.

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?

Two short paragraphs, purpose front-loaded, no filler. The field list is compact and readable.

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 structure need not be spelled out; the description still names the key fields, which is helpful. For a zero-argument read tool it is nearly complete, missing only ordering/pagination expectations.

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?

The tool takes zero parameters, so there is no parameter semantics to convey; baseline 4 applies. The description correctly makes no claims about inputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('List all courses the user is currently enrolled in on KodeKloud') and scopes it to the current user's enrollments, which separates it from get_course_outline and get_course_progress in spirit. It never names a sibling explicitly, so differentiation must be inferred.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no exclusions, and no mention of the obvious alternatives (get_course_progress for per-course detail, get_course_outline for a course's structure). The agent must guess when this list is the right starting point.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.