fabric_update_pipeline_definition

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

Annotations are empty, so the description carries the full burden. It mentions 'long-running' but does not clarify whether the operation is synchronous, async, or what the response model is. The word 'Replace' implies overwriting, but no details on partial vs full replacement are given.

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?

Single sentence, front-loaded with the core action and scope. No wasted words; efficient and to the point.

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?

For a mutation tool with 4 parameters and no output schema or annotations, the description is too brief. It omits behavior of the replace (e.g., does it clear existing data?), return value, error conditions, and operational context. More detail is needed for safe usage.

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 coverage is 100% so parameters are already described. The description adds nothing new about parameters beyond aggregating 'activities + parameters'. It meets the baseline for high schema 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 the verb (Replace), the resource (a pipeline's activities and parameters), and notes it is long-running. This distinguishes it from sibling tools like fabric_create_pipeline (create new) and fabric_run_pipeline (execute).

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?

No guidance on when to use this tool vs alternatives such as fabric_update_item_definition or fabric_create_pipeline. Missing prerequisites, conditions, or common scenarios, leaving the agent without decision support.

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