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hivelearn_list_quiz_questions

List all questions for a quiz, ordered by sort_order. Each question carries its options and correct answer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
quiz_idYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The description discloses that results are ordered by sort_order and that each question includes options and the correct answer. Since no annotations are provided, this adds valuable behavioral context beyond the basic 'list' operation, though it doesn't mention pagination or error conditions.

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 description is two concise sentences, front-loaded with the action, and contains no unnecessary information. Every clause adds value: the listing action, the quiz scope, the ordering, and the payload content.

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?

For a simple list operation with one parameter and no output schema, the description covers the essential return details: questions are ordered and include options and correct answer. It is sufficient for an agent to understand what the tool will return and how it behaves.

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?

The schema has a single quiz_id parameter with 0% description coverage in the schema. The description refers to 'for a quiz' which gives some context, but it doesn't explicitly name the parameter or explain its required format. The schema pattern provides format details. The description adds minimal compensating value.

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?

The description clearly identifies the tool as listing all questions for a quiz, with a specific verb and resource. It also distinguishes itself from sibling tools like list_quizzes (which lists quizzes) and get_quiz (which retrieves a quiz), as well as create/update quiz question tools.

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

Usage Guidelines3/5

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

The usage is implied: when you need all questions for a specific quiz. However, there is no explicit guidance on when to use this over alternatives like get_quiz or list_quizzes, and no exclusions or prerequisites are mentioned.

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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TDQS

A3.7/5.0
Disambiguation5/5

Every tool targets a distinct resource/action combination, and similar-looking tools are carefully differentiated in descriptions (e.g., get_course_structure vs list_course_modules, update_lesson vs update_lesson_content). There is no meaningful overlap or ambiguity between tools.

Naming Consistency5/5

All tools use a consistent 'hivelearn_<verb>_<noun>' pattern with common verbs (get, list, create, update). The only minor deviation is 'add' vs 'create' (add_track_course vs create_track), but this is semantically appropriate and does not disrupt the overall pattern.

Tool Count2/5

With 57 tools, the server is significantly over the recommended range and exceeds the 25+ threshold for 'too many'. While the broad domain (courses, community, analytics) justifies a large surface, this many tools makes selection overwhelming for agents and suggests a need for consolidation or sub-servers.

Completeness3/5

The tool surface covers create, read, and update for most core entities (courses, lessons, quizzes, tracks, posts, events, resources), plus publishing/verification and analytics. However, there are notable gaps: no delete operations for courses, lessons, modules, quizzes, posts, events, resources, or enrollments, and no way to remove a course from a track. These lifecycle holes are significant but not fatal for common workflows.

Resources