ai_pipeline_step_execute

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

No annotations are provided, so the description carries the full burden. It fully discloses the internal mechanism: lookup, context building, method call, and return of updated ctx. It also notes that composite_fields are populated by the step. While it does not detail potential side effects, the explanation is transparent about the operation.

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 very concise: two sentences with no unnecessary words. The first sentence states the core purpose, the second explains the process and includes a useful hint to a sibling tool. Front-loaded and efficient.

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 6 parameters (3 required) and no output schema, the description adequately explains the process and return value. It references the sibling tool for step discovery. It does not cover error handling or prerequisites like connection, but overall it is complete for an execution tool.

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 83%, so the baseline is 3. The description does not add significant new information beyond what is in the schema for parameters. It mentions the return value (updated ctx with populated composite_fields) but that relates to output, not parameters.

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 the action ('Execute a single ai.pipeline.step'), the resource ('by name via Odoo RPC'), and outlines the internal process. It distinguishes itself from sibling tools like ai_pipeline_steps_list by explicitly referencing it for discovering step names.

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 advises using ai_pipeline_steps_list to discover step names before execution, providing clear guidance. However, it does not mention when to use ai_pipeline_run instead (batch vs single step), which is a minor omission.

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