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analyze_model_geometry

Analyze a 3D model to detect overhangs, bridges, thin walls, and other slicer-critical regions, then generate optimized printing parameters.

Instructions

Detect geometric regions in a 3D model that affect slicing.

Analyzes model geometry to identify overhangs, bridges, thin walls,
top/bottom surfaces, fine details, and curved surfaces.  Each region
gets optimized slicing parameters in the adaptive plan.

Args:
    model_path: Path to an STL or 3MF file for analysis.
    model_stats: Pre-computed geometry statistics dict (from slicer
        preview or external tool).  Keys include ``height_mm``,
        ``overhangs``, ``bridges``, ``thin_walls``, etc.

Provide either ``model_path`` or ``model_stats`` (or both —
``model_stats`` takes precedence).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_pathNo
model_statsNo
Behavior3/5

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 analysis identifies specific geometric features and mentions parameter precedence. However, it does not describe the return format, potential side effects, permissions, or error cases. The behavioral disclosure is adequate but not comprehensive.

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?

The description is concise and well-structured. It starts with a clear purpose sentence, then lists Args with bullet points. Every sentence adds value without redundancy. No wasted words.

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 low complexity (2 parameters, no output schema, no annotations), the description is nearly complete. It covers purpose, parameters, and usage. The only gap is not describing the return format, but without an output schema, this is acceptable. The description provides sufficient context for an AI agent to understand and use the tool.

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

Parameters5/5

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

Schema coverage is 0%, so the description must compensate fully. It explains both parameters: model_path (path to STL/3MF file) and model_stats (pre-computed dict with example keys). It clarifies that either or both can be provided and that model_stats takes precedence. This adds significant meaning 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 clearly states the tool detects geometric regions affecting slicing (overhangs, bridges, thin walls, top/bottom surfaces, fine details, curved surfaces). It distinguishes itself from sibling tools like 'analyze_mesh_geometry' and 'analyze_printability' by focusing on slicing-specific geometry analysis. The verb 'Detect' and resource 'geometric regions in a 3D model' are specific and precise.

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

Usage Guidelines4/5

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

The description provides adequate usage context: use when needing to identify geometric features that affect slicing, with each region getting optimized slicing parameters. However, it does not explicitly state when not to use this tool or mention alternatives among sibling tools. The guidance is clear but lacks exclusions.

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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