Inspect the detailed contents of a dlt AI toolkit to understand its components and structure.
Show detailed contents of a dlt AI toolkit.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Name of the toolkit to inspect |
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| tags | Yes | ||
| rules | Yes | ||
| skills | Yes | ||
| version | Yes | ||
| commands | Yes | ||
| has_ignore | Yes | ||
| description | Yes | ||
| mcp_servers | No | ||
| dependencies | No | ||
| workflow_entry_skill | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description should disclose behavioral traits. It does not mention side effects, read-only nature, or any other behavioral aspects beyond a simple retrieval operation.
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?
The description is very concise with one sentence, no wasted words. However, it could be expanded slightly to include more context without losing conciseness.
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 simplicity of the tool (one parameter, output schema present), the description is minimally adequate. But considering sibling tools and lack of usage guidance, it's not fully complete.
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?
Schema coverage is 100% with a clear description for the single parameter. The tool description adds no additional semantic meaning beyond the schema, so baseline 3 is appropriate.
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 clearly states the verb 'Show' and the resource 'detailed contents of a dlt AI toolkit', distinguishing it from sibling tools like 'list_toolkits' which likely provide summaries, not details.
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?
No guidance on when to use this tool versus alternatives like list_toolkits or other inspection tools. Missing context about prerequisites or typical workflow.
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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