get_resource_usageShow your account's compute, database-RAM, and storage pools: how much you've bought, how much is used, and how much is free, plus every app's current size. Call this before any resize tool (the allowed sizes come from its steps fields), and to explain to the user why an app ran out of memory or a deploy was refused for capacity.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds behavioral context by detailing exactly what data is returned (bought, used, free, app sizes) and why it should be called, which enriches the agent's understanding beyond the annotations.
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 functionality and specific data categories, followed by a concise usage directive. Every sentence earns its place without redundancy.
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?
With no output schema, the description adequately enumerates the returned data categories and gives clear use cases, making it fully contextual for an agent selecting this tool among its siblings.
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, so schema coverage is trivially 100%. The description omits parameter details correctly, and no parameter semantics are needed; the baseline of 4 is appropriate for a parameterless tool.
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 'Show your account's compute, database-RAM, and storage pools' with specific data points (bought, used, free) and 'every app's current size'. It distinguishes itself from sibling tools by focusing on resource usage rather than deployment, logs, or resizing.
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 to call it 'before any resize tool' and 'to explain to the user why an app ran out of memory or a deploy was refused for capacity,' providing clear when-to-use guidance and implicitly referencing resize tools as alternatives.
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.