pbi_detect_circular_dependencies

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

With no annotations, the description carries full burden. It explains the algorithm (builds graph from DAX tokens, DFS for cycles, separate self-reports), providing good transparency. Could add details on output format or side effects, but overall sufficient.

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?

Two dense sentences with no wasted words. The first sentence states purpose, the second explains methodology. Ideal conciseness.

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's complexity (cycle detection in measures), the description covers the core algorithm and self-references. It lacks prerequisites or output details, but the presence of an output schema (not shown) reduces the need. Adequate overall.

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?

The schema has one parameter (include_hidden) with 0% description coverage. The description does not mention it at all, failing to compensate for the schema gap. For a simple boolean, even brief mention would raise the score.

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 detects cycles in the measure dependency graph, using the specific verb 'detect' and resource 'measure dependency graph'. This distinguishes it from siblings like pbi_measure_dependencies (which lists dependencies) and other detect tools.

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 use when circular dependencies are suspected in measures, but lacks explicit when-to-use or when-not-to-use guidance compared to siblings. No exclusions or alternatives are mentioned, which is a minor gap given the large sibling set.

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