regenerate_antenna_python_from_feedback

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

With no annotations, the description carries the full burden for behavioral disclosure. It only mentions the core function and the 'still without AEDT' constraint, but does not clarify side effects, whether it mutates state, permissions required, or what 'recorded feedback' refers to.

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, concise sentence with a clear verb-first structure. It contains no filler and communicates the essential action and constraint efficiently.

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 has only one parameter and no annotations, the description lacks crucial workflow context: what constitutes 'recorded feedback', what state the job must be in, and what 'next versioned' implies for the output. While an output schema exists, the description does not compensate for missing prerequisites or the feedback source.

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 description does not mention the job_id parameter at all, and schema coverage is 0%. It adds no meaning beyond the schema's minimal 'Job Id' title, failing to explain how to obtain or interpret the job_id in the context of this feedback-driven regeneration.

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 specific action: using recorded feedback to produce the next versioned Python model. It distinguishes from sibling tools like generate_antenna_python by emphasizing 'from feedback' and 'next versioned', making its purpose unique.

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 phrase 'from feedback' implies the tool should be used when feedback has been recorded, but it does not explicitly state when to use this tool versus alternatives like generate_antenna_python or refine_antenna_source. No exclusions or prerequisites are given.

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