start_data_source_run

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

No annotations provided, so description carries full burden. It mentions idempotency via client_token and lists return fields including status and errorMessage, but does not explicitly state whether the operation is destructive or read-only, nor any required permissions or side effects beyond creating a run.

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 well-structured with explicit Args, Returns, and Example sections. It is front-loaded with the purpose. However, it is somewhat verbose, especially with detailed return field listing, which could be condensed without losing clarity.

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?

The description comprehensively covers what the tool does, all parameters with constraints, and the return structure with detailed fields. There is no output schema, but the inline Return section provides equivalent information. The example adds practical context.

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 0%, but the description provides extensive parameter details: patterns for domain_identifier, explanation of client_token for idempotency, optionality, and length constraint. The example further clarifies usage, fully compensating for the schema gaps.

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 it 'Starts a data source run in Amazon DataZone' with a specific verb and resource. It distinguishes from related tools like create_data_source and get_data_source by focusing on starting a run, not managing the data source itself.

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 does not explicitly state when to use this tool versus alternatives or mention prerequisites like having an existing data source. It implies usage through parameter details and example but lacks guidance on when-not-to-use or sibling tool comparisons.

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