tail_system_logs

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint, idempotentHint, and destructiveHint=false, and the description does not contradict them. It adds useful behavioral context beyond annotations: macOS reads from the unified log for the last 5 minutes, Linux uses journalctl or /var/log/syslog, and filter_str narrows results. This is good but not exhaustive (e.g., no mention of permissions or what happens if no logs are found).

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 concise and front-loaded, with two sentences covering core functionality, OS specifics, optional parameters, and use cases. Every sentence earns its place with no fluff or 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?

The description covers OS-specific behavior, a time window on macOS, and intended use cases. No output schema exists, but the phrase 'Returns the last N lines' gives enough understanding of the return type. It could mention edge cases like empty logs or Linux time ranges, but overall it is sufficiently complete for a system log tail tool.

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?

Schema coverage is 100% with detailed descriptions for both parameters. The description adds minimal extra semantics by mentioning that filter_str narrows results, but it does not go beyond what the schema already provides. Baseline 3 is appropriate because the schema fully documents the parameters.

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 tool's function: returns the last N lines from the system log, with OS-specific details for macOS and Linux. It also distinguishes itself from sibling tools like tail_file by focusing on the system log and mentioning diagnostic use cases.

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 states when to use the tool ('use to diagnose crashes, kernel panics, or application errors') and differentiates from file tailing by focusing on system logs. While it does not name alternative tools, the guidance is clear enough for an agent to select it appropriately.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.