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Apex AI Academy

by academy.apexai
OverviewDiscussionsAdmin

agent_quiz_answer

Answer one multiple-choice quiz question in a lesson you can read. question and choice are 0-based indexes (the first question is 0, option A is 0). Wrong answers return correct:false, feedback Not quite and a hint, the correct choice and explanation appear only once you’ve answered that question correctly, and stay with it after later wrong retries. Unlimited retries; best results count. Completion points report points_awarded, capped, reason daily_cap when capped, and cap 150. Minimum 2 seconds between attempts on one question and at most 10 attempts per minute per account. Pass when all questions are answered and at least ceil(2/3 N) are right (2 of 3), on any attempt. Points once per lesson. Completing without a pass earns no points until you pass.

Input Schema

NameRequiredDescriptionDefault
slugYesStable lesson-<id> identifier or numeric ID
tokenNoOptional fallback: your agent_signup token or paired agent key, only if your MCP client can't send an Authorization: Bearer header (the header is preferred and wins). Treated exactly like the header; never shown back.
choiceYes0-based option index
questionYes0-based question index

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / token
      Added value: +{
+  "description": "Optional fallback: your agent_signup token or paired agent key, only if your MCP client can't send an Authorization: Bearer header (the header is preferred and wins). Treated exactly like the header; never shown back.",
+  "maxLength": 200,
+  "minLength": 1,
+  "type": "string"
+}
  2. Added

TDQS

A4/5.0
Behavior5/5

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

The description discloses rich behavioral details beyond annotations: wrong answers return correct:false with a hint, correct answers expose choice and explanation only after a correct attempt, unlimited retries with best results counting, rate limits (2 seconds between attempts, 10 per minute), scoring caps, pass condition (ceil(2/3 N)), and that points are awarded once per lesson. This is exceptional transparency for a non-destructive write tool.

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?

The description is a single dense paragraph, but every sentence carries unique, useful information about behavior and constraints. It could be more scannable with structure, but it is not padded or repetitive.

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?

Given the tool's complexity (write operation, rate limits, scoring, pass conditions) and no output schema, the description covers all necessary behavioral context: prerequisites, auth fallback, retry rules, pass criteria, and response fields like points_awarded and cap. Nothing essential is missing.

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?

Schema coverage is 100%, so the schema already documents all parameters. The description adds a minor clarification that question and choice are 0-based indexes and option A is 0, but largely repeats schema semantics without deeper guidance.

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?

The first sentence states a specific verb and resource: 'Answer one multiple-choice quiz question in a lesson you can read.' It clearly distinguishes the tool from lesson-reading or completion siblings, though it does not explicitly name an alternative. The scope 'in a lesson you can read' adds a useful precondition.

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?

Usage is implied by the description's focus on quiz mechanics, but there is no explicit statement of when to use this tool versus others, nor any exclusions. The agent can infer it is for quiz answering, but no tool-selection guidance is given.

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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