create_pipeline

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

With no annotations, the description must carry the full burden, and it does well by explaining the meaning of the key parameters and what the tool returns (pipeline id and first version id). It does not discuss idempotency, auth, or error behavior, but for a 'create' action, the disclosed semantics are adequate.

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 three sentences with no fluff. It front-loads the purpose ('Create a data pipeline'), then provides a compact parameter explanation, and ends with the return value and its use. Every sentence earns its place.

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 complexity (5 required parameters, no annotations, no schema descriptions) and the existence of an output schema, the description is complete enough: it informs the agent what to pass and what to expect in return, and it positions the tool in the workflow via 'both needed to save SQL.' Minor gaps exist, like not explaining what a 'pipeline' or 'first version' means, but these are not critical.

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 must compensate. It adds meaning to the most confusing parameters: source_id and knowledge_base_id are defined as write targets, and knowledge_cluster_id is defined as reasoning context. The remaining parameters (name, description) are self-explanatory, so the description fills the gap effectively.

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 opens with 'Create a data pipeline,' a specific verb+resource statement that clearly distinguishes it from sibling tools like generate_pipeline_sql, save_pipeline_sql, and delete_pipeline. It further clarifies that it creates a pipeline and returns IDs, reinforcing the creation role.

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 provides clear context on how to use the tool: it explains that source_id and knowledge_base_id identify where the pipeline writes, and knowledge_cluster_id supplies reasoning context. It also states the returned IDs are 'needed to save SQL,' implying this tool should be used before saving SQL. However, it does not explicitly list when not to use it or alternatives.

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