list_appsList the apps in your Dockhold account, with each app's id, status, URL, and source repo. Call this first whenever the user asks about their apps, or when you need an app_id for any other tool.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds value by disclosing the return payload fields and the tool's role as a first-step lookup, which is beyond what annotations convey.
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 two sentences, front-loaded with the core purpose, and contains no redundant wording. Every clause adds meaningful information: what is listed, which fields are returned, and when to call it.
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?
For a parameterless list tool with strong annotations, the description is complete: it names the resource, return fields, and primary use case. No output schema exists, but the return fields are explicitly listed, which adequately covers what the agent needs to know.
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 tool has zero parameters, and the baseline for 0 params is 4. The description adds no parameter-specific details because there are none to describe; the empty schema already fully covers 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 states a specific verb ('List') and resource ('apps in your Dockhold account'), and enumerates the returned fields (id, status, URL, source repo). This clearly distinguishes it from sibling tools like list_github_repos and get_app_status.
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?
Explicitly instructs when to use the tool: 'Call this first whenever the user asks about their apps, or when you need an app_id for any other tool.' This provides clear contextual guidance and positions it as a prerequisite for other app-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct operation: deployment, monitoring, scaling, configuration, or listing. There is no overlap; agents can easily select the correct tool.
All tools follow a consistent verb_noun pattern in snake_case (e.g., deploy_app, get_app_logs, resize_database). No naming irregularities.
12 tools cover the core operations of a deployment platform without bloat or missing essentials. The count is well-scoped.
Covers deploy, manage, scale, and monitor effectively. Missing only minor operations like deleting an app or environment variable, but the core workflow is complete.