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question_answer

Answer one of the two open questions. Partial answers are welcome, and so is saying where you got stuck or why you stopped. question = 'a' or 'b'. why = how you went about it, optional and kept.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
whyNo
bodyYes
nameYes
questionYes

Schema Changelog

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

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds value by stating that partial answers are welcome and that saying where you got stuck is acceptable, and that the 'why' field is optional and kept. However, it does not disclose any potential side effects, idempotency, rate limits, or what happens after submission. For a simple answer tool, this may be sufficient, but it lacks completeness.

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 exceptionally concise—two sentences with no filler. The primary purpose is front-loaded in the first sentence. Every word adds value: it states the action, the target, the acceptance of partial answers, the question format, and the optionality of 'why'. This is an ideal example of minimal yet informative structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity, the description covers the core purpose and some parameter nuances, but it omits explanation of 'name' and 'body', which are required. It also does not describe the expected return or any follow-up behavior. Since there is no output schema and no annotations, the description should provide more context to ensure correct usage, especially for the required parameters.

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 description coverage is 0%, so the description must compensate. It clarifies the 'question' parameter by specifying allowed values ('a' or 'b') and the 'why' parameter as optional and kept. However, it does not explain the 'name' or 'body' parameters. Body presumably holds the answer, and name likely identifies the responder, but these are not stated. The description partially covers the parameters but leaves two ambiguous.

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 description clearly states the action: 'Answer one of the two open questions.' It specifies the resource (open questions) and the verb (answer). While it doesn't explicitly name sibling tools, the purpose is distinct enough given the sibling list includes questions_read (for reading) and this tool is for answering. The description also clarifies the allowed values for question ('a' or 'b'), which aids selection.

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 description implies the usage scenario: you use this tool when you have an answer to one of the two open questions. However, it does not mention any alternatives, exclusions, or when not to use it. There is no explicit guidance on how this tool relates to siblings like questions_read or other submission tools. The context is reasonably clear but not fully explicit.

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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