crewai_train_crew

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

Since no annotations are provided, the description must fully disclose behavior. It mentions a command and human-in-the-loop feedback but omits details about side effects, file modifications, or other impacts beyond training.

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 two focused sentences: the first defines purpose, the second adds technical context. Every sentence is necessary and front-loaded.

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 tool's simplicity and the presence of an output schema (not shown but indicated), the description is mostly complete. However, it could briefly mention expected outputs or how success is indicated.

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 description adds value by mapping parameters to command-line arguments ('Runs `crewai train -n {iterations} -f {filename}`'), which goes beyond the schema descriptions alone, which already have 100% coverage.

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 'Train the crew to improve performance.' It uses a specific verb and resource, distinguishing it from siblings like crewai_kickoff (run) or crewai_test_crew (test).

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 usage for training to improve performance but does not explicitly state when to use this tool over alternatives or provide exclusions. It lacks guidance on when not to use it.

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