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codeofaxel

Kiln

by codeofaxel
OverviewSchemaRelated ServersScoreDiscussions
Python

estimate_price

Estimate 3D printing costs instantly by specifying technology, part volume or dimensions, and quantity.

Instructions

Get an instant price estimate before requesting a full quote.

        Args:
            technology: Manufacturing technology: FDM, SLA, SLS, MJF, or DMLS.
            volume_cm3: Part volume in cubic centimeters (if known).
            dimensions_x_mm: Bounding box X dimension in mm (alternative to volume).
            dimensions_y_mm: Bounding box Y dimension in mm.
            dimensions_z_mm: Bounding box Z dimension in mm.
            quantity: Number of copies (default 1).

        Returns a low/high price range based on typical per-cm3 pricing for
        the technology.  For exact pricing, use ``fulfillment_quote`` with a
        real model file.

        Either ``volume_cm3`` or all three dimension parameters must be provided.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
quantityNo
technologyYes
volume_cm3No
dimensions_x_mmNo
dimensions_y_mmNo
dimensions_z_mmNo

Tool Definition Quality

A4.5/5.0
Behavior3/5

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

No annotations provided, but description explains return value (low/high range based on typical pricing) and calculation method. Lacks details on auth, rate limits, or caching, but sufficient for a simple estimation 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?

Well-structured with summary, parameter list, and return info. Clear but slightly verbose; 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?

Given 6 parameters, no output schema, and no annotations, the description is complete: explains parameters, constraints, return type, and differentiation from sibling.

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%, but description explains all parameters: technology options, volume vs. dimensions, quantity default, and the mutual exclusivity constraint. Adds significant meaning beyond 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?

Description clearly states 'Get an instant price estimate' with specific verb and resource, and distinguishes from sibling tool 'fulfillment_quote'.

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?

Explicitly states when to use (before full quote) and when not (for exact pricing, use fulfillment_quote). Also provides required parameter constraint.

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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