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

With no annotations, the description carries full responsibility for behavioral disclosure. It only mentions 'rule-based', which implies determinism, but does not state whether the tool is read-only, what inputs are essential, or what the feedback output looks like.

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 no redundant wording. However, it is under-specified, but conciseness is about efficiency, and this sentence is efficient in conveying the core purpose.

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?

For a tool with eight parameters, no output schema, and no annotations, this description is severely incomplete. It provides only a high-level purpose and leaves the agent without enough information to reliably construct valid inputs or interpret the response.

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 parameter-level meaning. The eight parameters, including required 'process' and 'quantity', are left entirely unexplained, so the agent must rely on property names alone.

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 that the tool provides design-for-manufacturability feedback for a part specification, which distinguishes it from sibling tools like estimate_bom or request_quote. While the verb 'feedback' is less specific than 'generate' or 'provide', the resource and focus are clear.

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 given on when to use this tool versus alternatives such as compare_processes or refine_quote. There are no context cues, exclusions, or prerequisite conditions, leaving the agent to infer usage from the name alone.

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