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solve_template_constraints

Solves parametric constraints for 3D model templates, adjusting parameters to meet size and ratio limits.

Instructions

Solve parametric constraints to find valid template parameters.

        Given a template and constraints (min/max/equals/ratio), iteratively
        adjusts parameters to satisfy all constraints while staying within
        the template's declared parameter ranges.

        :param template_id: Template identifier (e.g., "shelf_bracket").
        :param constraints: JSON object mapping param names to constraint dicts.
            Example: ``{"width": {"min": 20, "max": 50}, "height": {"equals": 30}}``
            Supported keys: min, max, equals, ratio (e.g. ``{"ratio": ["width", 0.5]}``).
        :returns: Dict with solved_params, satisfied/violated constraints.
        

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
constraintsYes
template_idYes
Behavior3/5

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

With no annotations, the description reveals that the tool 'iteratively adjusts parameters' and returns solved/violated constraints. It does not disclose potential side effects, performance limits, or error handling, but covers the core behavior adequately for a solver tool.

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

Conciseness4/5

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

The description is structured with a one-line summary followed by detailed explanation and parameter definitions. It is slightly verbose but every sentence adds value. Could be more concise without losing clarity.

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 tool's complexity (solving constraints), the description explains the iterative algorithm, constraint format, and return structure. It does not cover unsolvable cases or timeout behavior, but covers the essential aspects well for an agent.

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?

The schema coverage is 0%, but the description provides detailed semantics for both parameters: template_id with an example ('shelf_bracket'), and constraints with a full JSON example and supported keys (min, max, equals, ratio). This compensates fully for the missing schema descriptions.

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 states a specific verb 'Solve' and resource 'parametric constraints' with a clear goal 'to find valid template parameters'. It immediately conveys the tool's purpose and distinguishes it from other tools like 'generate_template_variations' or 'optimize_template_params' by focusing on constraint solving.

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

Usage Guidelines2/5

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

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or when not to use it. Without explicit usage context, the agent may struggle to select the correct tool among siblings like 'optimize_template_params'.

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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