get_app_logsGet the most recent runtime logs for one app. Call this when an app is crashing, returning errors, or a deploy succeeded but the app misbehaves: the logs usually name the cause.
| Name | Required | Description | Default |
|---|---|---|---|
| tail | No | Number of recent log lines to return (max 200, default 100) | |
| app_id | Yes | The app id returned by list_apps |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior, so the description does not need to repeat safety. It adds value by explaining that logs are diagnostic ('the logs usually name the cause') and that they are the 'most recent' runtime logs, which is useful behavioral context 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 with no fluff. The first sentence states the core function, and the second provides usage context. Every word earns its place, making it concise and well-structured.
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 simple read-only log retrieval tool with full schema coverage and strong annotations, the description provides adequate context for when to use it. It lacks details about output format or pagination, but these are not critical for the tool's purpose, so it is nearly 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?
The input schema provides 100% parameter descriptions for 'app_id' and 'tail', so the description does not need to add param semantics. It adds nothing beyond the schema, so the baseline of 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 ('Get'), the resource ('runtime logs'), and the scope ('for one app'), distinguishing it from sibling tools like deploy_app or get_app_status. It explicitly names the action and the object, leaving no ambiguity about what the tool does.
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?
The description gives explicit when-to-use guidance: 'Call this when an app is crashing, returning errors, or a deploy succeeded but the app misbehaves.' It does not name alternative tools, but the context makes it clear that this is the diagnostic log tool, distinct from deployment or status tools, so it falls just short of a 5.
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.