validate_design_for_requirements

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

No annotations are provided, so the description carries full burden. It discloses that the tool performs checks and returns pass/fail with suggestions, but it does not mention whether it is read-only, authentication needs, or response format details. It partially covers behavioral traits but lacks completeness.

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 concise, with each sentence adding value. However, it lacks a structured front-loaded summary; it is presented as a single paragraph with line breaks. Still, no redundant information is present.

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?

The description covers core functionality, usage context, and next steps. However, it omits details on return format (e.g., list of checks, pass/fail structure), error handling, and what happens with invalid inputs. Without an output schema, these gaps reduce 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 coverage is 0%, so the description compensates by explaining file_path (STL/OBJ), requirements (same as another tool), and material (optional with example). This adds significant value beyond the schema's bare titles, though it omits validation rules or constraints.

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 tool validates a 3D model against functional design requirements, specifying it checks structural, dimensional, and manufacturability constraints. It distinguishes itself from sibling tools like analyze_design_requirements and analyze_mesh_geometry by focusing on post-generation validation.

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 'Call this AFTER generating a model and BEFORE printing it' and provides guidance to use fix suggestions for regeneration. However, it does not mention when not to use it or contrast with other validation tools like validate_gcode or validate_mesh.

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