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get_active_labs

List active interactive KodeKloud hands-on lab sessions with status, remaining lease time, and access URLs to monitor running, paused, or stopped labs before expiration.

Instructions

List active interactive hands-on labs with status and remaining lease time.

Inspects currently provisioned or running lab sessions (Running, Paused, Stopped), remaining time before automatic expiration, and access URLs.

Returns: ActiveLabsResponse with active lab session details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesCount of currently active or provisioned labs.
errorNoError message if the operation or upstream request failed.
warningNoDiagnostic warning or configuration guidance message.
active_labsNoList of active lab sessions.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully enumerates the states inspected (Running, Paused, Stopped) and mentions automatic expiration, which signals this is a read-only listing. However, it does not state that it is non-mutating, nor does it cover pagination or rate/scope limits, which would matter for an agent deciding how to call it.

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?

Front-loaded with the purpose sentence, then a compact breakdown of what is inspected, then the return type. It is slightly longer than strictly necessary because the 'Returns' block largely restates what the first two sentences already covered, but it is not wasteful.

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 the description need not explain return structure in depth, and it correctly keeps return description light. For a zero-parameter read listing, the remaining gap is the absence of usage guidance and any statement of the operation's read-only nature, but coverage is otherwise adequate.

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?

There are zero parameters, so the baseline is 4. The description correctly adds no parameter noise and instead documents return fields, which is appropriate for a parameterless listing tool.

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 (List) and resource (active interactive hands-on labs) with the returned fields named (status, remaining lease time). It does not reference any sibling tool, but the resource is specific enough that an agent can distinguish it from get_course_progress or list_enrolled_courses.

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?

No when-to-use or when-not-to-use guidance is given. The description explains what the tool returns but never says under what circumstances an agent should prefer this over other lab/session related calls, or what triggers its use.

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