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route_print_job

Routes a print job to the optimal printer in the fleet by scoring material match, build volume, availability, and quality-speed preference.

Instructions

Route a print job to the best available printer in the fleet.

        Scores each printer based on material match, build volume, availability,
        and quality/speed preference, then recommends the optimal assignment.

        Args:
            file_path: Path to the file to print.
            material: Required filament material (e.g. "PLA", "PETG").
            quality: Quality preference — "draft", "standard", or "fine".
            priority: Job priority — "low", "normal", or "high".
        

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qualityNo
materialNo
priorityNo
file_pathYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It ambiguously says 'routes' and 'recommends' without clarifying whether the tool actually submits the job or only suggests an assignment. Side effects, authentication needs, and mutability are not addressed.

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 extremely concise, with two short paragraphs and a clean args list. No unnecessary details, and the purpose is front-loaded.

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

Completeness3/5

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

The description covers the main purpose, scoring criteria, and parameters, but lacks information about the return value (what is output?), error cases, and prerequisites (e.g., printer fleet configuration). An output schema would have helped but is absent.

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 0%, so the description compensates by explaining each parameter (file_path, material, quality, priority) with examples. However, it does not specify allowed values formally, leaving room for ambiguity.

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

Purpose4/5

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

The description clearly states the tool's purpose: to route a print job to the best available printer by scoring based on material, build volume, availability, and quality/speed preference. It is specific about the verb and resource, but does not explicitly distinguish from similar sibling tools like suggest_printer_for_job.

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 provides no guidance on when to use this tool versus alternatives (e.g., suggest_printer_for_job, optimize_fleet_assignment), nor does it specify prerequisites or when not to use it.

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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