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Dpanel Compose Get From Git

dpanel_compose_get_from_git

Retrieves a Docker Compose file from a Git repository, enabling AI agents to deploy or update projects in DPanel.

Instructions

从 Git 仓库拉取 compose 文件。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uriYes
nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.11.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It states that the tool pulls a compose file from Git but does not disclose authentication requirements, whether it writes/overwrites local compose data, what 'name' controls, or any side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single front-loaded sentence with no wasted words. It is structurally clean, though the extreme brevity borders on under-specification for a tool with two undocumented required parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

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. But with no annotations, no schema parameter descriptions, and no sibling differentiation, the one-line description leaves key invocation details missing for a two-required-parameter tool.

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

Parameters1/5

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 for both required parameters 'uri' and 'name'. It supplies no meaning for either parameter, leaving the agent unable to determine expected formats or the role of 'name' beyond guesswork.

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 gives a specific verb (拉取/pull) and resource (compose 文件) and names the source (Git 仓库), so the basic operation is clear. It does not mention the sibling dpanel_compose_get_from_uri, so an agent must infer the contrast from the source wording rather than being explicitly routed.

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 source phrase '从 Git 仓库' implies when this tool is applicable: when the compose file should come from a Git repository. However, there is no explicit when-not guidance and no named alternative such as dpanel_compose_get_from_uri.

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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