search_logs

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

The description adds value beyond the annotations by noting that the tool returns 'a breakdown of error types' alongside matching entries. Annotations already indicate read-safe, non-destructive, idempotent behavior, which aligns with the description. No contradictions.

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 consists of two efficient sentences. The first sentence covers function and filters; the second covers output and use case. No redundant or vague wording.

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 5 parameters and no output schema, the description adequately covers inputs and hints at output (entries + error breakdown). It does not elaborate on the breakdown structure, but the purpose is clear for an agent to select and invoke the tool correctly. Sibling tools are numerous, but the description doesn't compare; still, it's sufficient.

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 5 parameters are described in the input schema (100% coverage). The description lists filter categories (status, status class, path, recipient) but does not add details beyond what the schema already provides (e.g., default for sample, exact vs. class differentiation). Baseline score of 3 is appropriate.

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 verb 'search' or 'fetch' and the resource 'API request logs', and distinguishes from siblings like 'get_log' (single log) and 'list_logs' (all logs) by specifying the filtering capability and the focus on recent 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?

The description provides a clear use case: 'Use to find why requests are failing.' While it doesn't explicitly state when not to use it or mention alternatives, the context of troubleshooting failures is well-established, and the tool's filtering options align with that purpose.

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