pbi_profile_data

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

The description states 'Solo lectura' (read-only), but the annotations set `readOnlyHint: false`. This is a direct contradiction, undermining the agent's ability to trust the tool's side-effect profile. Although other behavioral details are provided (detected issues, queries, consequences), the contradiction forces a score of 1 per evaluation rules.

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 well-structured and concise, with each sentence providing essential information: purpose, complementary relationship, detection criteria, and parameter roles. No filler; it is front-loaded and stays focused.

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 moderate complexity, the description covers the key aspects: what it does, which specific data anomalies it detects, what each finding includes, that it is read-only, and how parameters affect behavior. The presence of an output schema means return values need no explanation, so this description is complete for agent usage.

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%, so the description fully compensates by explaining both parameters: `tables` scopes the work, and `max_columns` prevents timeout on large models. This adds meaningful context beyond the bare type information in the schema.

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 uses a specific verb 'Perfila' (profiles) with a clear resource ('VALORES del modelo'), and explicitly distinguishes itself from pbi_audit_model by stating it reviews data values rather than structure. This makes the tool's purpose unmistakable and differentiates it from its sibling.

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 explains when to use this tool instead of pbi_audit_model, noting that structural audits miss data-level issues like percentages outside 0-100. It also provides practical usage guidance for parameters, such as using `tables` to limit scope and `max_columns` to avoid timeouts.

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