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suggest_material_for_order

Suggests optimal material and technology for a fulfillment print order based on use case, budget, and requirements like weather resistance, food safety, or detail.

Instructions

Suggest a material when ordering a print from a fulfillment provider.

        Use this when routing a print job to a fulfillment provider
        and need to pick the right material + technology for the order.

        **Which material tool to use:**

        - Ordering a print from a service? → ``suggest_material_for_order`` (this tool)
        - Designing a part and need engineering specs? → ``recommend_design_material``
        - Quick intent-based pick for your own printer? → ``recommend_material``

        Args:
            use_case: What the part is for. Options: decorative, functional,
                mechanical, prototype, miniature, jewelry, enclosure, wearable,
                outdoor, food_safe.
            budget: Price preference: "budget", "mid", or "premium". Empty = any.
            need_weather_resistant: Only recommend weather-resistant materials.
            need_food_safe: Only recommend food-safe materials.
            need_high_detail: Prefer high-detail materials (SLA/MJF).
            need_high_strength: Prefer high-strength materials (SLS/MJF).

        Returns ranked material recommendations with technology, reasoning,
        price tier, and which fulfillment provider to use.
        

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
budgetNo
use_caseYes
need_food_safeNo
need_high_detailNo
need_high_strengthNo
need_weather_resistantNo
Behavior4/5

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

No annotations are provided, so the description fully bears the burden. It discloses that the tool returns ranked recommendations with technology, reasoning, price tier, and provider. However, it does not mention any edge cases (e.g., no matching material) or permission requirements. Still, the behavior is sufficiently clear for a suggestion tool.

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 well-structured with a clear heading, usage instructions, a bulleted parameter list, and a return description. It is concise with no wasted words, every sentence adds value.

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

Completeness5/5

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

The tool has 6 parameters, 1 required, and no output schema. The description covers all parameters, explains the return value (ranked recommendations with technology, reasoning, price tier, provider), and distinguishes from sibling tools. It is complete for the intended usage.

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 has 0% description coverage, but the description adds detailed semantics for all parameters: use_case with enumerated options, budget with three values, and boolean flags. This goes well beyond the schema's minimal titles and types.

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 suggests a material when ordering a print from a fulfillment provider. It uses specific verbs and resources and distinguishes itself from sibling tools like 'recommend_design_material' and 'recommend_material' by specifying the ordering context.

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

Usage Guidelines5/5

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

The description explicitly says 'Use this when routing a print job to a fulfillment provider' and provides a table clarifying which material tool to use for different scenarios, offering clear when-to-use and when-not-to-use guidance.

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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