compare_co_scientist_workflows

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

No annotations are present, so the description must carry full behavioral disclosure burden. It implies a read-only comparison operation, but does not describe the output format, return value, side effects, or any data requirements beyond accepting result dicts.

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 cleanly structured: purpose, automatic triggers, parameter. Every line contributes useful information and the decision contexts are front-loaded with no filler.

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?

Since there is no output schema and no annotations, the description should clarify what the tool returns or how the comparison is presented, but it never does. It gives enough trigger information for selection, but not enough for an agent to know what to do with the result.

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?

The schema only says 'array of objects' with 0% coverage, so the description adds useful meaning by distinguishing workflow result dicts from pre-evaluated result dicts. However, it does not specify the expected keys or what distinguishes a raw result from a pre-evaluated one, so compensation is only partial.

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 ('Compare') and resource ('benchmark results across workflow types'), and enumerates the three workflow types involved. This clearly distinguishes it from sibling tools like evaluate_co_scientist_run or get_co_scientist_benchmark_tasks.

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?

Provides explicit automatic trigger conditions, including the decision context of whether the simpler workflow should remain default. It lacks explicit when-not-to-use guidance or named alternatives, so it falls just short of a 5.

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