WAzion MCP Server

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

With no annotations provided, the description carries the full burden. The '[mutation]' tag correctly signals a write operation. However, it fails to specify critical behavioral traits: whether updates are partial (omitted fields preserved) or full replacement, what happens if the ID doesn't exist, or whether the operation is reversible.

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 appropriately sized (one sentence + metadata tag) and front-loaded with the action 'Update'. The em-dash creates slight redundancy ('Update' = 'Edit'), but remains readable. The '[mutation]' tag efficiently conveys behavioral classification without annotation support.

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 100% schema coverage and lack of output schema, the description adequately covers the tool's purpose and domain. It appropriately omits return value details (no output schema exists), though it could improve by mentioning error handling behavior or partial update semantics for the optional parameters.

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 100%, with all 4 parameters (id, fact_content, category, status) fully documented in the schema. The description adds domain context ('customer-facing WhatsApp AI') but does not add parameter-specific syntax, format constraints, or enum values beyond what the schema already provides (e.g., status values 'active or rejected'). Baseline 3 is appropriate.

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 'Update[s] Customer AI Correction' and specifies it 'Edit[s] an existing correction for the customer-facing WhatsApp AI'. This specific scope (WhatsApp AI vs general AI) distinguishes it from sibling `update_ai_error`, and 'existing' distinguishes it from `set_customer_ai_error` (likely for creation).

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 by stating 'Edit an existing correction', suggesting it requires a pre-existing record ID. However, it lacks explicit when-to-use guidance (e.g., 'Use this to modify existing corrections; use set_customer_ai_error to create new ones') or prerequisites.

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