aedt_call

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

With no annotations, the description carries full burden for behavioral disclosure. It only mentions 'public' methods but does not describe side effects, permissions, error behavior, or limitations. It fails to add meaningful behavioral context.

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 a single sentence, making it concise, but it is too sparse for a complex 7-parameter tool. It sacrifices necessary detail for brevity.

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 high complexity (7 parameters, many optional) and the existence of an output schema (not disclosed), the description should provide more context. It does not explain return values or usage patterns, making it insufficient for correct invocation.

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 is expected to compensate. However, it offers no parameter details. While parameter names like 'target', 'method', 'args' are somewhat self-explanatory, 'attr_path' and 'module_name' remain ambiguous without explanation.

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 it invokes public PyAEDT or AEDT native methods for broad API coverage, which conveys a general-purpose invocation tool. However, it does not differentiate from sibling tools like 'aedt_native_module_call' or 'aedt_batch_call', missing an opportunity to clarify its specific role among similar generic tools.

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 is provided on when to use this tool versus the many specialized sibling tools (e.g., aedt_analyze, aedt_create_geometry). The description lacks any when-nots or alternative suggestions, leaving the agent without selection criteria.

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