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learn_question
Read-only

Everything the bank teaches about a question the player has already answered or looked up: the stem, options, key, the player's pick, the explanation, why each wrong option is wrong, the longer teaching note and the concept map. Pays and changes nothing.

Input Schema

NameRequiredDescriptionDefault
questionIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description reinforces that with 'Pays and changes nothing.' It also discloses the full return contents, including the player's pick, explanation, wrong-option rationales, teaching note, and concept map. It does not discuss error behavior for unanswered questions or access requirements, but the annotation coverage lowers the burden.

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 single sentence is front-loaded with the core purpose and then lists exactly what the tool teaches. Despite being long, every clause contributes useful return-value context, and there is no filler.

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?

With no output schema, the description does the necessary work by enumerating what is returned. It also states the key precondition and the no-side-effect behavior. The remaining gap is the lack of questionId format or provenance, which is relevant because schema coverage is 0%.

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 sole parameter is questionId, and schema description coverage is 0%, so the description must carry the meaning. It implies that the ID must refer to a question the player has already answered or looked up, which is useful validity context, but it does not specify the identifier format or how to obtain it.

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 states a specific resource and scope: 'everything the bank teaches about a question the player has already answered or looked up,' and enumerates the returned content. It clearly distinguishes itself from answer_question and look_up_answer by focusing on post-answer/learning material rather than answering or looking up a fresh question.

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

Usage Guidelines4/5

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

It gives a clear usage prerequisite: the question must have already been answered or looked up. It also states 'Pays and changes nothing,' which separates it from answer_question. However, it does not explicitly name look_up_answer as the alternative for questions that have not yet been answered.

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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