summarize_logs

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

No annotations are provided, so the description must fully disclose behavior. It mentions output aggregates and env requirements but lacks details on whether the tool is read-only, error handling, or performance implications. Destructive potential is not addressed.

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, with a clear lead sentence followed by structured argument list. It avoids fluff, though the first sentence is a fragment. The layout is easy to scan.

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?

Inputs are well-covered, and the output schema exists (not shown) so return values need not be detailed. However, missing guidance on mutually exclusive parameters (path vs index), edge cases, and error states reduces completeness.

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 0%, so the description carries full weight. It explains each parameter (path, index, query, time_from, time_to, limit) with context like local file vs API index, Lucene query, ISO timestamps, and default limit. This adds significant meaning beyond the schema.

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 aggregates log summaries including top endpoints, error rates, slowest requests, and unique IPs. It also specifies two modes (file or API index), making the purpose distinct from sibling tools like query_logs or get_errors.

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 explains when to use file mode vs API mode and mentions required env variable for API. However, it does not explicitly differentiate from siblings or state when not to use this tool (e.g., when raw logs are needed).

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