docker_log_summary

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

With no annotations, the description carries the full burden. It explicitly states read-only behavior and that aggregation happens client-side without leaving logs. It also lists possible errors. However, it could mention authentication requirements or rate limits, but given the context, this is sufficiently transparent.

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 and well-structured. It front-loads the purpose, then provides parsing behavior, client-side note, output format, and error list without any redundant sentences.

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 complexity (conditional parsing, multiple output fields), the description is quite complete. It covers both modes, output keys, and errors. However, it lacks guidance on performance or limits (e.g., maximum lines scanned) and does not specify how the tool determines if logs look like access logs.

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 100%, so the baseline is 3. The description adds value by explaining that 'top_n' applies to each section (top_paths and error_patterns) and by outlining the overall output structure, which helps understand how parameters affect results.

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 one container's log stream with specific parsing behaviors for access logs and error-pattern grouping. It distinguishes the tool from siblings like 'get_logs' or 'docker_logs' by focusing on summarization rather than raw log retrieval.

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 implies use when needing aggregated log summaries and describes internal conditional behavior, but it does not explicitly state when to use this tool versus alternatives like 'cloudwatch_get_log_events' or 'journal_errors'. No when-not or alternative tools are mentioned.

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