cldkctl_notebook_images
List available notebook images for data science and machine learning workflows on the Cloudeka platform.
Instructions
Call the cldkctl_notebook_images endpoint
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List available notebook images for data science and machine learning workflows on the Cloudeka platform.
Call the cldkctl_notebook_images endpoint
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states 'Call the... endpoint,' which reveals nothing about the operation's nature (e.g., read vs. write, side effects, permissions, rate limits, or output format). This is inadequate for a tool in a system with potentially destructive operations (e.g., delete tools in siblings).
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?
While concise with one sentence, the description is under-specified rather than efficiently informative. It wastes its single sentence on a tautology ('Call the... endpoint') that adds no value beyond the tool name. In a context with many sibling tools, this brevity fails to convey necessary meaning, making it ineffective.
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?
Given the complexity implied by the sibling tools (e.g., notebook and VM management) and the lack of annotations and output schema, the description is severely incomplete. It doesn't explain what the tool does, its behavior, or its output, leaving the agent unable to use it correctly. This is inadequate even for a simple tool in this ecosystem.
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 input schema has 0 parameters with 100% coverage, meaning no parameters need documentation. The description doesn't add parameter details, which is acceptable here—it doesn't compensate for gaps because there are none. A baseline of 4 is appropriate as the schema fully handles the parameter semantics.
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 'Call the cldkctl_notebook_images endpoint' is tautological—it restates the tool name with 'call' as a generic verb, failing to specify what the tool actually does. It doesn't distinguish this tool from its many siblings (e.g., cldkctl_notebook_list, cldkctl_notebook_create) or clarify whether it lists, creates, or manages notebook images. This provides minimal actionable information beyond the name.
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 offers no guidance on when to use this tool versus alternatives. With siblings like cldkctl_notebook_list and cldkctl_notebook_create, it's unclear if this tool is for listing available images, creating new ones, or another purpose. There's no mention of prerequisites, context, or exclusions, leaving the agent with no usage direction.
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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