hivelearn_get_question_bank
Fetch one question bank with its item_count. Items are listed separately via hivelearn_list_question_bank_items.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Fetch one question bank with its item_count. Items are listed separately via hivelearn_list_question_bank_items.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It discloses two useful traits: the response includes item_count and does not include the items themselves. It does not describe error behavior, permissions, or whether the count is live, but as a simple fetch operation it is adequately transparent for most agent use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no filler. The primary purpose is front-loaded, and the pointer to the sibling tool is placed second, keeping the highest-value information first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The definition is complete enough for a single-id fetch: it states what is returned, what is not returned, and how to get the omitted items. It would be stronger with an explicit note on not-found behavior or a fuller description of the question bank object, but it covers the core invocation context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage and only one required 'id' parameter with a UUID format. The description implies that 'id' identifies the question bank being fetched, but it does not add explicit parameter-level semantics. For a single, self-evident identifier this is sufficient, though not richly explanatory.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('Fetch one question bank') and adds a distinctive detail ('with its item_count'), which separates it from list-style siblings. It also explicitly names the related item-listing tool, eliminating ambiguity between this and hivelearn_list_question_bank_items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly routes the agent to hivelearn_list_question_bank_items when the items themselves are needed, which is helpful usage guidance. However, it does not explicitly contrast this with hivelearn_list_question_banks, so the when-to-use guidance is slightly incomplete.
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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