pbi_column_dependencies

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

The readOnlyHint annotation already indicates a safe read operation, so the description's added context—listing dependency types and the 'tells if something breaks' behavior—provides meaningful transparency beyond the annotation. No contradictions found.

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 two concise sentences, front-loaded with the core purpose and followed by a practical use case. Every word earns its place without fluff.

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?

The description covers the essential use case and dependency types, and an output schema likely documents return values. It lacks details like interpretation of results or limitations, but given the schema and annotations, it is sufficiently complete for the tool's complexity.

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?

With 0% schema description coverage, the description must explain parameters, but it only indirectly references 'column' and 'table' without detailing them. The 'source' parameter is not mentioned at all, leaving ambiguity about its purpose (e.g., live vs. other sources).

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 identifies what uses a column—measures, calculated columns, relationships, and hierarchies—which is a specific verb+resource. It also distinguishes itself from sibling tools like pbi_measure_dependencies by focusing on column dependencies rather than measure dependencies.

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 explicitly says to use it before hiding or deleting a column to check if anything breaks, providing a clear when-to-use scenario. It doesn't mention when not to use it or name alternatives, but the context is specific enough for agents to select it appropriately.

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