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Glama

trivia

by io.github.pipeworx-io

Get Questions

get_questions
Read-onlyIdempotent

Get trivia questions from the Open Trivia Database. Optionally filter by category, difficulty, and question type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoQuestion type. One of: multiple (multiple choice), boolean (true/false).
amountNoNumber of questions to return. Defaults to 10. Max 50.
categoryNoCategory ID to filter by. Use list_categories to get available IDs.
difficultyNoDifficulty level. One of: easy, medium, hard.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNumber of questions returned
questionsYesArray of trivia questions

Schema Changelog

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

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "count": {
+      "description": "Number of questions returned",
+      "type": "number"
+    },
+    "questions": {
+      "description": "Array of trivia questions",
+      "items": {
+        "properties": {
+          "category": {
+            "description": "Trivia category name",
+            "type": "string"
+          },
+          "correct_answer": {
+            "description": "The correct answer",
+            "type": "string"
+          },
+          "difficulty": {
+            "description": "Question difficulty level",
+            "type": "string"
+          },
+          "incorrect_answers": {
+            "description": "Array of incorrect answer options",
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "question": {
+            "description": "The trivia question text",
+            "type": "string"
+          },
+          "type": {
+            "description": "Question type (multiple or boolean)",
+            "type": "string"
+          }
+        },
+        "required": [
+          "category",
+          "difficulty",
+          "type",
+          "question",
+          "correct_answer",
+          "incorrect_answers"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "count",
+    "questions"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "amount": 10
+  },
+  {
+    "amount": 5,
+    "category": 9,
+    "difficulty": "hard",
+    "type": "multiple"
+  }
+]
  3. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety and mutability. The description adds no extra behavioral details (e.g., return limits, error behavior) beyond what annotations provide, so it is consistent but not enriching.

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 one concise sentence that front-loads the core action and mentions optional filters without waste. Every word earns its place.

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?

The tool is a simple read-only retrieval with only optional parameters. The schema defines all parameters and output schema exists, so the description need not explain return values or parameter syntax; it provides enough context for selection.

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 input schema has 100% coverage with each parameter described (type, amount, category, difficulty). The description merely summarizes 'filter by category, difficulty, and question type' without adding detail beyond the schema, so a baseline score of 3 is appropriate.

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 states the tool retrieves trivia questions from the Open Trivia Database and allows optional filters by category, difficulty, and type. This specific verb+resource combination distinguishes it from sibling tools like list_categories or suggest_questions.

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?

The description does not provide any comparison or exclusion relative to sibling tools. It implies usage when trivia questions are needed, but lacks explicit guidance such as 'use this instead of suggest_questions when you need questions from the Open Trivia Database'.

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

A3.6/5.0
Disambiguation2/5

Several tools have notably unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and polymarket_edges, polymarket_arbitrage, and bet_research heavily overlap in surfacing betting opportunities. Entity_profile, recent_changes, and compare_entities also share overlapping research scope, making misselection likely.

Naming Consistency3/5

Most names use snake_case and a roughly readable verb_noun style (resolve_entity, compare_entities, list_categories), but conventions vary: some are bare nouns (entity_profile), some are plain verbs (remember, forget), and ask_pipeworx/pipeworx_* break the pattern. It is readable overall, but not a consistent scheme.

Tool Count2/5

34 tools is far more than the 'trivia' name implies, and most of them (Pipeworx research, Polymarket analysis, memory, subscriptions) are unrelated to trivia. The set reads as an entire platform bundled together rather than a purpose-scoped server.

Completeness2/5

For the stated trivia purpose, the surface is missing core lifecycle features like quiz sessions, answer validation, or scoring; the few trivia tools are just category/reference lookups. As a general data/research server it is broad, but there are significant gaps and no coherent domain model tying the tools together.

Resources