WAzion MCP Server

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

Without annotations, the description carries the full burden. It discloses that the tool analyzes distributions of specific conversation attributes (satisfaction, urgency, intentions), which hints at the return format. However, it lacks disclosure on safety (read-only status), performance characteristics, rate limits, or what happens when called with no parameters (all optional).

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 compact and front-loaded with the resource and key metrics. However, the trailing '[query]' appears to be a template artifact or placeholder that creates confusion without adding value, slightly undermining the structural quality.

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?

With no output schema provided, the description should ideally characterize the return structure (e.g., percentage distributions, counts by category). It also fails to explain default behavior when no filters are applied (all time? last 30 days?). Given 4 optional parameters, this gap is significant.

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 input schema has 100% description coverage, establishing a baseline of 3. The description adds no additional parameter context (e.g., explaining that 'days' and 'date' are mutually exclusive, or how 'phone' filters the results), but the schema adequately documents each field.

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 identifies the specific metrics provided: satisfaction distribution, urgency, and intentions ('Distribucion de satisfaccion, urgencia e intenciones'). This distinguishes it from generic siblings like `get_analytics` or `get_sentiment_analysis`. However, the '[query]' artifact at the end appears to be a placeholder error, and it doesn't explicitly differentiate from `get_structured_analytics` or `get_sentiment_analysis` which may overlap in functionality.

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 provided on when to use this tool versus the numerous sibling analytics tools (`get_analytics`, `get_sentiment_analysis`, `get_structured_analytics`, `get_sentiment_trend`). No mention of prerequisites or whether this aggregates historical data versus real-time data.

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