linux_logsRead system logs from journalctl and syslog to diagnose Linux infrastructure issues, identify errors, and correlate events with host, Nginx, Docker, and PostgreSQL activity.
Чтение системных логов (journalctl, syslog)
| Name | Required | Description | Default |
|---|---|---|---|
| params | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral disclosure burden. It only says 'reading', which suggests a non-destructive operation, but it doesn't disclose whether the tool executes journalctl/syslog commands, requires elevated privileges, accepts filters, or what the output format is.
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 a single short phrase, which is concise in length but severely under-specified. It omits crucial parameter and usage semantics. This is under-specification rather than effective conciseness.
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 tool with a free-form params schema, no annotations, and no visible output schema details, the description is incomplete. It identifies the domain but fails to explain how to invoke the tool, what parameters to use, what behavior to expect, or how the output is structured.
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 has a single free-form 'params' object (additionalProperties: true, 0% coverage), providing no semantic guidance. The description doesn't explain that params likely map to journalctl/syslog options or filters, so an agent cannot know what to pass in. The description adds zero value beyond the schema's generic object.
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 ('reading') and resource ('system logs'), and names concrete backends (journalctl, syslog). This clearly distinguishes it from nginx/k8s/docker log tools, though it doesn't explicitly differentiate from service_logs.
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?
No guidance on when to use this tool versus alternatives. It doesn't mention that this is for host-level system logs rather than service-specific logs, nor does it point to log_search/log_tail as potential alternatives. Usage context is only implied by the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.