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coolify_logs

Retrieve application logs from Coolify infrastructure management by specifying the application UUID and optional line count for monitoring and debugging purposes.

Instructions

Application logs and monitoring - get application logs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAction to perform: get (get application logs)
uuidYesApplication UUID (required for get action)
linesNoNumber of log lines to retrieve (optional for get action)

Implementation Reference

  • The primary handler function for executing the 'coolify_logs' tool. It validates the UUID, constructs the API endpoint for fetching application logs (with optional lines parameter), calls the Coolify API client, and returns the logs as formatted JSON text content.
    async logs(action: string, uuid: string, lines?: number) {
      if (!uuid) throw new Error('Application UUID is required for logs action');
      
      switch (action) {
        case 'get':
          const endpoint = lines ? `/applications/${uuid}/logs?lines=${lines}` : `/applications/${uuid}/logs`;
          const response = await this.apiClient.get(endpoint);
          return { content: [{ type: 'text', text: JSON.stringify(response.data, null, 2) }] };
        default:
          throw new Error(`Unknown logs action: ${action}`);
      }
    }
  • The input schema definition for the 'coolify_logs' tool, specifying the required 'action' (only 'get'), 'uuid', and optional 'lines' parameters.
      name: 'coolify_logs',
      description: 'Application logs and monitoring - get application logs',
      inputSchema: {
        type: 'object',
        properties: {
          action: { 
            type: 'string', 
            enum: ['get'],
            description: 'Action to perform: get (get application logs)'
          },
          uuid: { 
            type: 'string', 
            description: 'Application UUID (required for get action)' 
          },
          lines: { 
            type: 'number', 
            description: 'Number of log lines to retrieve (optional for get action)' 
          },
        },
        required: ['action', 'uuid'],
      },
    },
  • src/index.ts:108-109 (registration)
    The switch case in handleToolCall that registers and dispatches 'coolify_logs' tool calls to the appropriate handler method.
    case 'coolify_logs':
      return await this.handlers.logs(args.action, args.uuid, args.lines);
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 burden of behavioral disclosure. It states the tool is for 'get application logs' but doesn't describe what 'get' entails—e.g., whether it returns real-time or historical logs, if there are rate limits, authentication requirements, or pagination behavior. The mention of 'monitoring' in the description is vague and adds little actionable context, leaving significant gaps in understanding the tool's behavior.

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 concise with two phrases ('Application logs and monitoring' and 'get application logs'), which are front-loaded and to the point. However, 'Application logs and monitoring' is somewhat redundant with 'get application logs', and the monitoring aspect isn't elaborated, slightly reducing efficiency. Overall, it avoids unnecessary verbosity but could be more streamlined.

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?

Given the complexity of a logging tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the logs contain (e.g., format, timestamps), how to interpret them, or any limitations (e.g., log retention periods). With siblings like coolify_application_lifecycle that might overlap, more context is needed to ensure the agent can use this tool effectively without confusion.

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

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with clear documentation for each parameter (action, uuid, lines). The description adds no additional meaning beyond what's in the schema—it doesn't explain parameter interactions (e.g., how lines affects output) or provide examples. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract from the schema's clarity.

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 clearly states the tool's purpose as 'get application logs', which is a specific verb+resource combination. It distinguishes this tool from siblings like coolify_application_deployments or coolify_application_lifecycle by focusing on logs rather than deployments or lifecycle management. However, it doesn't explicitly differentiate from all siblings (e.g., monitoring aspect isn't clarified versus other tools).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, such as needing an application UUID from another tool like coolify_applications, or specify scenarios where logs are needed (e.g., debugging vs. monitoring). With siblings like coolify_application_lifecycle that might involve logs, the lack of explicit usage context leaves the agent guessing.

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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