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moldsim
by moldsim

generate_dfm_checklist

Generate DFM checklists for injection molded parts to validate 15+ design rules. Analyzes wall thickness, draft angles, ribs, and materials to return pass/warn/fail status and identify manufacturing risks.

Instructions

Generate a Design for Manufacturability (DFM) checklist for an injection molded part. Returns pass/warn/fail status for 15+ design rules based on part description and parameters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionYesDescription of the part (e.g., "Automotive connector housing with snap-fits and thin walls")
wall_thickness_mmNoNominal wall thickness in mm
rib_thickness_mmNoRib thickness in mm
rib_height_mmNoRib height in mm
draft_angle_degNoDraft angle in degrees
materialNoMaterial name or ID (e.g., "PA66-GF30", "ABS")
has_undercutsNoWhether the part has undercut features
has_textureNoWhether surfaces are textured
texture_depth_mmNoTexture depth in mm (for draft calculation)
gate_typeNoGate type: "edge", "sub", "pin", "hot", "fan", "tunnel"
cosmetic_requirementsNoWhether part has cosmetic surface requirements
Behavior4/5

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

With no annotations provided, the description carries the full burden and successfully discloses the return format (pass/warn/fail status) and evaluation scope (15+ design rules), though it omits error handling behavior and side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences efficiently communicate purpose and return behavior without redundancy. Every word earns its place, with no filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema, the description appropriately discloses the return structure. With 100% schema coverage handling inputs, the description is nearly complete, though noting that only 'description' is required while other parameters are optional would improve it further.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, establishing a baseline of 3. The description references 'part description and parameters' generically without adding semantic meaning, relationships between parameters (e.g., rib-to-wall thickness ratios), or input examples beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description provides a specific verb ('Generate'), clear resource ('Design for Manufacturability checklist'), and domain ('injection molded part'), effectively distinguishing it from siblings like validate_process_parameters and compare_materials.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

While the domain specificity ('injection molded part') provides implicit context, the description lacks explicit when-to-use guidance or differentiation from siblings like validate_process_parameters that also operate in the manufacturing domain.

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

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