data_author_pipeline

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

The annotations already indicate destructive, non-idempotent, read-write behavior. The description adds useful context that execution routes through the domain-agent dispatcher under JWT, tenant, and company scope, but it does not disclose what side effects occur, what gets created or modified, or how outputs are returned. There is no contradiction with the annotations.

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, front-loaded with the action name, and organized clearly into scope and args sections. It has no unnecessary filler, though the opening sentence is somewhat tautological and leaves the real purpose unstated.

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?

Even with an output schema and annotations, the description is incomplete for agent decision-making: it never states what author_pipeline does, when to prefer it over similar data tools, or what practical outcome to expect. The routing and scope note helps, but the core semantics of the action are missing.

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%, so the description carries the burden of explaining parameters. It does explain message as a free-text objective and inputs as an optional JSON string of structured inputs, which is meaningful beyond the schema. It lacks examples or details about the expected JSON structure, but for two simple parameters this is adequate.

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 has a verb and resource ('Run the data domain agent action author_pipeline') and places it in the data domain, but it never says what author_pipeline actually accomplishes. The first sentence largely restates the tool name, so an agent must infer what 'author' means and how it differs from data_run_pipeline or data_submit_job.

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?

There is no guidance on when to use this tool compared to the many relevant sibling tools such as data_run_pipeline, data_submit_job, or dispatch_domain_agent. No conditions, exclusions, or alternatives are mentioned, leaving selection entirely to inference.

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