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. It discloses the mutation nature via '[mutation]' tag and the dangerous operation requiring confirmation. However, it fails to mention side effects (e.g., immediate availability to AI), reversibility, or what happens when adding a function that already exists (overwrite vs error).

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 single-sentence description efficiently packs multiple information layers: purpose, scope (AI-callable APIs), mutation classification, and confirmation requirement. The em-dash structure creates clear separation between the high-level purpose and implementation details. Only minor improvement would be separating the confirmation instruction for readability.

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 provides minimum viable context. It adequately explains what the tool configures but lacks information about success indicators, partial failure behavior, or the immediate impact on AI behavior. For a mutation tool affecting AI capabilities, additional context on execution effects would strengthen completeness.

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%, providing detailed Spanish descriptions for all three parameters (add_function, remove_function, confirm). The description text mentions the confirmation parameter requirement ('pasar confirm=true'), but this merely echoes the schema description. With complete schema coverage, 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 identifies the resource (custom AI functions) and their purpose (APIs the AI can call during conversations). It uses 'Define' effectively in the second clause, though the opening verb 'Configurar' is slightly broad. It distinguishes from sibling update_* tools which modify existing entities, whereas this creates/configures callable function definitions.

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 states the confirmation requirement ('requiere confirmación: pasar confirm=true'), which is crucial for this mutation tool. However, it lacks guidance on when to use add_function vs remove_function, or when to prefer this tool over other configuration tools like apply_prompt_instruction. No alternative tools or prerequisites are mentioned.

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