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 and does well: it declares 'Read-only', discloses that aggregation is client-side and raw logs never leave the operator, and enumerates the failure modes (docker_not_available, docker_permission_denied, container_not_found, no_logs_available). It stops short of describing rate limits or scan cost.

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?

Front-loaded with the aggregation purpose, followed by mode behavior, privacy note, result shape and errors. Dense but each clause carries distinct value; not padded.

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?

No output schema exists, yet the description spells out the returned JSON fields (kind, status_mix, error_rate_4xx/5xx, top_paths, error_patterns, lines_scanned) and the named error set, so an agent knows both what it gets and how it fails.

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 instance_id, container, top_n and since_minutes are already documented with ranges and defaults. The description adds no constraint meaning beyond that, so the baseline 3 applies.

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?

States a specific verb (aggregate) and resource (one container's log stream) and immediately signals its distinction from a raw-log sibling by naming the two summarization modes. An agent can tell this apart from docker_logs without opening a schema.

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 the internal conditions under which it switches parsing modes, which is useful behavior context, but never states when to choose this over docker_logs or docker_events_summary. Usage is implied rather than routed.

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