pbi_validate_model

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

With no annotations, the description carries full burden. It discloses that the tool performs an audit and lists check categories, implying it's read-only and returns results. However, it does not mention permissions, connection requirements, or side effects. Adequate but not comprehensive.

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?

One sentence efficiently listing example checks. No wasted words, though it could front-load the main purpose more explicitly. Overall concise.

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?

Tool is simple (one param, output schema exists). Description lists checks performed, which is sufficient for a validation tool. It doesn't need to explain output since schema exists. Minor gap: no mention of the parameter, but otherwise complete.

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%. The single parameter include_warnings is not mentioned in the description, so the description adds no meaning beyond the schema. With such low coverage, the description should compensate, but it fails to do so.

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?

Description clearly states the tool audits the model for common issues, listing specific examples like empty expressions, missing format strings, orphan tables, duplicate measure names. It ties to the name 'validate_model' and distinguishes from siblings like pbi_audit_model by specifying the type of checks.

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?

No guidance on when to use this tool versus alternatives (e.g., pbi_audit_model, pbi_lint_dax). No description of prerequisites, context, or situations to avoid. The agent is left to infer applicability.

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