dpanel_setting_getRetrieves a DPanel configuration item by group name and setting name, enabling AI agents to read specific system or Docker settings for management tasks.
读取 DPanel 配置项。group_name 如 setting；name 如 DPanelInfo/docker。
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| group_name | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v1.11.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. '读取' (read) weakly implies a safe read, but nothing is said about permissions, behavior when a key is missing, or value formats; the only added context is example parameter values.
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 compact sentences, front-loaded with the action and resource, then the parameter examples. No filler, though the parameter hint could be integrated more cleanly.
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?
An output schema exists, so return values need not be described. For a two-parameter getter the definition is serviceable, but with 0% schema coverage the lack of an explanation of key/group conventions leaves an agent guessing at valid inputs.
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 description coverage is 0%, so the description must compensate, and it partially does by giving a concrete example for each parameter (group_name='setting', name='DPanelInfo/docker'). However it never explains the valid domain of groups or the dotted/slash key structure, leaving the format largely inferable only from the examples.
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 states a specific verb (读取/read) and resource (DPanel 配置项/config item), so an agent immediately knows this fetches a config value rather than mutating or listing one. It does not explicitly differentiate itself from any sibling, though no other setting-read sibling exists in the list.
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?
There is no guidance on when to use this tool versus alternatives, nor any prerequisites or context for the lookup. The example key values hint at the use case but stop short of stating a usage condition.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.