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list_notebooks

Read-only

Lists all available DeepTutor notebooks for review and selection.

Instructions

List DeepTutor notebooks

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes原始 DeepTutor 工具返回值;其具体字段由对应 DeepTutor API 决定。

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.1/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read. The description adds no further behavioral context such as ordering, depth, or scope, but for a parameterless list operation this is a minor omission.

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?

A single, front-loaded sentence that wastes no words. Every token contributes meaning.

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 absence of parameters, the read-only annotations, and the presence of an output schema, the description contains everything needed to invoke the tool correctly. No return-value documentation is required because an output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema description coverage is 100%, so there is nothing left for the description to document. Per the baseline for parameterless tools, this is effectively complete.

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 uses a specific verb ('List') and a clear resource ('DeepTutor notebooks'), immediately distinguishing this collection-returning tool from siblings like get_notebook, create_notebook, and list_books. No ambiguity remains about what operation is performed.

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 verb 'List' implies this is the collection-level retrieval tool, while siblings like get_notebook handle individual notebooks. However, the description gives no explicit guidance on when to choose this over those alternatives or whether any filtering is available.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.