Skip to main content
Glama

ncloud_hadoop_list_notebook_components

Read-only

List available notebook components for Cloud Hadoop, including Jupyter versions, by region and image product code. Use to identify options for configuring notebooks.

Instructions

List available notebook components (e.g. Jupyter versions)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionCodeNoRegion code
cloudHadoopImageProductCodeNoImage product code filter
Behavior3/5

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

The readOnlyHint annotation declares this is a safe read operation, and the description is consistent with that. The description adds minimal context beyond the annotation—only the example of Jupyter versions hints at what the response contains. No additional behavioral details (pagination, auth, return structure) are disclosed.

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?

One short, front-loaded sentence with zero wasted words. The verb 'List' leads immediately, and the parenthetical example adds useful specificity without bloat.

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?

For a simple read-only list operation with full schema coverage and a readOnlyHint annotation, the description is minimally adequate. However, with no output schema, it could have explained the response format, and given the sibling tools, it could have clarified how 'components' differs from 'images' and 'products'.

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 100%, so both parameters (regionCode, cloudHadoopImageProductCode) are already documented in the schema. The description adds no parameter-level meaning, meeting the baseline of 3 when the schema carries the full burden.

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 uses a specific verb ('List') and identifies the resource as 'available notebook components' with a concrete example ('Jupyter versions'). However, it does not explicitly distinguish this from sibling tools like ncloud_hadoop_list_notebook_images or ncloud_hadoop_list_notebook_products, leaving potential ambiguity about what 'components' includes.

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

Usage Guidelines2/5

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

No when-to-use guidance is provided. The description does not mention when this tool should be chosen over the similar Hadoop notebook listing siblings (list_notebook_images, list_notebook_products), nor does it note any prerequisites or exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sjk4425/ncloud-gov-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server