test_log_parsing_rule

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

No annotations are provided, so the description carries the full burden. It mentions the automatic generation of a grok_pattern when not provided, which is useful behavioral context. However, it lacks details on permissions, rate limits, response format, or error handling for a testing tool with 3 parameters, leaving significant gaps in transparency.

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 highly concise and front-loaded: two sentences with zero waste. The first sentence states the core purpose, and the second adds critical behavioral context. Every word earns its place, making it easy to scan and understand quickly.

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?

Given the tool has an output schema (which handles return values) and no annotations, the description is partially complete. It covers the basic purpose and one behavioral trait but misses parameter details and broader context like error scenarios or integration with siblings. For a testing tool with 3 parameters, this leaves room for improvement.

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 description coverage is 0%, so the description must compensate. It only addresses 'grok_pattern' by noting it can be omitted for auto-generation, but it doesn't explain 'log_samples' (e.g., format, size limits) or 'account_id' (e.g., purpose, when required). With 3 parameters and low coverage, this is insufficient.

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 purpose: 'Test a log parsing rule against sample logs.' It specifies the verb ('Test') and resource ('log parsing rule') with context ('against sample logs'). However, it doesn't explicitly differentiate from sibling tools like 'generate_log_parsing_rule' or 'create_log_parsing_rule' beyond the testing focus.

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 implied usage guidance: 'If no grok_pattern is provided, it will generate one automatically.' This suggests when to omit the parameter, but it doesn't explicitly state when to use this tool versus alternatives like 'generate_log_parsing_rule' or 'create_log_parsing_rule', nor does it mention prerequisites or exclusions.

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