correlate_logs_and_metrics

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

No annotations are provided, so the description carries the full behavioral burden. It describes the intended analysis outcome but does not disclose whether the tool is read-only, what permissions or backend availability are required, how expensive the combined query is, or what happens when one data source fails.

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 short and front-loaded, stating the core correlation purpose in the first sentence. The second sentence is somewhat generic and partially repeats the incident/root-cause framing, but it remains concise overall.

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?

With an output schema present, the description does not need to explain return values, and the input schema is fully documented. However, the absence of annotations and any usage guidance leaves gaps around when to use this tool versus related log/metric tools and what operational behavior to expect.

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 100%, so the input parameters are already well documented as LogQL, PromQL, and a time window. The description adds only the high-level idea of combining Loki and Prometheus, without additional parameter semantics 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 states a specific verb and resource: correlate log entries with metrics for incident analysis, combining Loki and Prometheus. This is clearer than a generic observability tool, but it does not explicitly distinguish itself from siblings such as query_loki_logs or collect_performance_metrics.

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 phrase 'for comprehensive incident analysis' and 'root cause analysis' implies when the tool is useful, but there is no explicit guidance on when to choose it over querying logs or metrics separately. No exclusions or named alternatives are provided.

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