get_error_log

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

With no annotations, the description discloses key behaviors: default stacktrace truncation and filter options. It is transparent about the truncate_traces parameter's effect, though it could mention that the tool is read-only.

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 very concise: one introductory sentence, a clear parameter list, and two examples. No unnecessary text, 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?

All 5 parameters are explained with examples, but the description lacks details on the return format (e.g., fields in the log entries). Given no output schema, slightly more completions would be ideal.

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 description adds significant meaning beyond the schema: it explains each parameter's purpose, value range, and defaults (e.g., limit 1-100, level values 'ERROR' or 'WARNING'). The schema itself has no descriptions, making this essential.

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 it retrieves the Home Assistant error log via WebSocket API, specifying a specific resource. It distinguishes from sibling tools like get_core_logs by focusing on errors and stacktraces.

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 provides context for usage via examples and parameter descriptions, but does not explicitly guide when to use this over alternatives like get_core_logs or set_log_level.

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