get_service_logs

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

Annotations already mark the operation read-only and idempotent; the description adds the key behavioral detail that since_minutes is anchored to the simulation's current time (14:06 UTC) rather than wall-clock time. It also reveals that logs include stack traces and patterns, and there is no contradiction with 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?

Three sentences, no redundant filler. The main purpose is front-loaded, and each subsequent sentence adds either usage or parameter context.

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 straightforward log-read tool with no output schema, the description covers purpose, usage, time semantics, and level filtering. It doesn't describe the response format, but that's not required when no output schema exists and the use case is clear.

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?

All three parameters have full schema descriptions (100% coverage), so the description adds marginal value. The notable addition is clarifying the simulation-time reference for since_minutes, which is not in the schema. Filter-by-level guidance is a usage tip rather than new semantics.

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 clear verb-resource pair ('Retrieves error logs') with service and time-window scoping. It also distinguishes itself from sibling tools like get_service_metrics or check_pod_status by focusing on log content for troubleshooting.

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 agents to use it after a symptom is observed and to filter for ERROR/FATAL during incidents. It implies the tool is for post-incident log inspection, but doesn't explicitly name alternative tools or exclusion cases.

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