pbi_measure_dependencies

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

The description adds significant behavioral context beyond the readOnlyHint and openWorldHint annotations. It discloses that the analysis is lexical, detecting only written references and not dynamically constructed ones, which is a critical limitation. It also mentions the inclusion of broken references, providing useful insight into the tool's behavior.

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 concise and well-structured. It opens with a one-line summary of the tool's purpose, followed by two sentences that detail the outputs and the lexical analysis limitation. Every sentence adds valuable information without unnecessary verbosity.

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 core functionality comprehensively: direct dependencies, transitive closure, reverse dependencies, and lexical limitations. An output schema exists, so return values need not be described. The main gap is the unexplained `source` parameter, which prevents a perfect score.

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 0% description coverage, leaving the burden on the description. The description explains that `depth` controls the transitive closure depth and implicitly identifies `name` as the measure name. However, the `source` parameter is not explained at all, leaving a gap in understanding what values it accepts and how it affects the analysis.

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's purpose: it returns measure dependencies, both direct and transitive, plus reverse dependencies. It distinguishes itself from siblings like pbi_column_dependencies by focusing on measures. The phrase 'De que depende una medida y quien depende de ella' captures the bidirectional dependency analysis.

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 understanding measure dependencies but does not explicitly state when to use this tool over alternatives such as pbi_column_dependencies or pbi_run_dax. There is no when-not-to-use guidance or mention of alternative tools. The context is clear enough for an informed agent, but the lack of explicit exclusions prevents a higher score.

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