pbi_analyze_model_quality

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

Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds a list of concrete quality checks, which provides useful context. However, it does not disclose additional behavioral traits such as how results are returned, model loading requirements, or performance implications.

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 front-loaded: the first sentence summarizes the core purpose, and the second sentence is a compact list of checks. Every sentence earns its place with no redundant phrasing.

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 output schema exists, so return value details are not necessary. The description provides a solid list of checks, but it omits parameter semantics and usage context, and it does not clarify how this tool relates to similar audit/diagnostic siblings. Given the tool's complexity, this is a moderate gap.

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 single parameter 'source' has a default 'live' but no schema description, and the tool description does not mention or explain it. With 0% schema description coverage, the description fails to compensate or add any meaning to the parameter, leaving agents guessing about valid values or behavior.

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 typical model quality problems ('Detecta problemas tipicos del modelo (calidad)') and lists specific checks (measures without folder, long DAX, bidirectional/inactive relationships, calculated columns, visible IDs, missing calendar). This is a specific verb+resource and gives concrete scope, though it does not explicitly differentiate from overlapping siblings like pbi_audit_model.

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?

There is no guidance on when to use this tool versus alternatives. With many sibling tools for auditing (pbi_audit_model, pbi_health_check, pbi_diagnose_data), the description only states what it checks, not when to choose it over others or what prerequisites exist.

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