pbi_create_contribution_measure

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

No annotations are provided, so the description must carry the full burden. It explains the DAX formula but does not disclose behavioral traits such as overwrite behavior, authorization needs, or side effects. The tool modifies the model, but this is not explicitly stated.

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 extremely concise with two sentences and a code block. It front-loads the purpose and provides a clear DAX template with example usage. No wasted words.

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 tool has 7 parameters with no schema descriptions, the description is not complete. It explains the logic of the contribution measure but does not clarify the role of each parameter or return value. With a sparse 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 description coverage is 0%, so the description must compensate. It provides meaning for scope_columns with an example but does not explain the other 6 parameters (table, base_measure, measure_name, overwrite, format_string, display_folder). Only partial semantic value is added.

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 tool creates a %-of-total contribution measure. It provides the DAX template and explains the denominator scope, making it distinct from generic create-measure siblings like pbi_create_measure or other specialized measures.

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 implies usage for creating contribution measures with a specific DAX pattern but does not explicitly state when to use this tool versus alternatives like pbi_create_measure. No exclusions or when-not-to-use guidance is given.

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