aedt_run_app_method

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

No annotations are available, so the description carries full responsibility. It does not disclose side effects, authentication requirements, error handling, or what happens if the method does not exist or arguments are invalid. The presence of an output schema is not reflected.

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 with no overhead, which is efficient. However, the minimalism crosses into under-specification, reducing its helpfulness.

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 generic nature and the presence of an output schema, the description is incomplete. It omits important context such as the object's available methods, argument formats, and typical usage patterns. For an AI agent, this is insufficient.

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%, and the description adds no information about the meaning of 'method', 'args', or 'kwargs'. The agent must infer entirely from parameter names, which is insufficient for correct invocation.

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 verb 'call' and the resource 'public method on active PyAEDT app object'. It is concise and indicates the tool is for invoking generic methods on the app object, but it does not distinguish from sibling tools like 'aedt_call' or 'aedt_batch_call'.

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 alternatives. With many sibling tools (e.g., aedt_call, aedt_batch_call) and other specialized operations, the absence of usage context leaves the agent to guess.

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