Diff logs between two executions

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

No annotations are provided, so the description carries full behavioral burden. It discloses the normalization tolerance, the three output categories, and the counts, giving a clear picture of what the tool does beyond the raw schema.

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?

Three sentences, front-loaded with the core action, followed by output details and use case. No wasted words; every sentence provides value.

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?

Despite having no output schema and no annotations, the description fully explains what is returned, the normalization logic, and the intended use case. It is complete for a tool of this complexity.

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%, but the parameter names executionIdA and executionIdB are self-explanatory. The description consistently uses A and B to refer to the two executions, clarifying their roles in the diff. It does not add format/type details, but the naming plus context is sufficient.

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 diffs two executions' logs, specifies the grouping method (normalized source, level, message), and describes the return categories. This is a specific verb+resource that distinguishes it from siblings like execution_get_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?

Explicitly frames this as the flaky-test-style debugging tool, instructing to run the same thing with execution_run and compare a failing run against a passing one. This tells the agent when to use it and gives a concrete workflow.

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