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Kiln

by codeofaxel
OverviewSchemaRelated ServersScoreDiscussions
Python

check_print_health

Check the health of an active 3D print. Verifies printer connectivity, temperature accuracy, print progress, and error state in a single quick query. Optionally evaluates adhesion risk.

Instructions

Perform a single-shot health assessment of the current print.

        Unlike ``watch_print`` (which starts a background monitoring
        thread), this tool runs one check cycle and returns immediately.
        It is designed for quick "is the print OK right now?" queries
        from an agent without starting persistent background tasks.

        Checks performed:

        * **Printer connectivity** — is the printer online?
        * **Temperature** — are hot-end and bed within 15 °C of target?
        * **Print progress** — current completion, layer count, ETA.
        * **Error state** — any active firmware error codes.

        If *model_path* is supplied, adhesion risk is also evaluated via
        ``analyze_printability``.

        Args:
            printer_name: Named printer to query.  Omit for the default.
            model_path: Optional path to the model being printed.
                Enables geometry-based adhesion risk analysis.
            material: Filament material (e.g. ``"PLA"``, ``"ABS"``).
                Passed to adhesion analysis when *model_path* is provided.
            printer_id: Printer model ID (e.g. ``"bambu_a1"``).
                Used for printer-intelligence lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
materialNo
model_pathNo
printer_idNo
printer_nameNo

Tool Definition Quality

A4.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the checks performed (connectivity, temperature, progress, error state) and mentions adhesion analysis if model_path is supplied. However, it does not explicitly state that the tool is read-only or has no side effects, which is important for a health assessment 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: a concise introductory sentence, a bullet list of checks, and a clear 'Args:' section. It is front-loaded with the core purpose and contrast to watch_print. Every sentence adds value without unnecessary verbosity.

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 has 4 optional parameters, no enums, no output schema, and no nested objects, the description covers the tool's behavior and parameter usage well. It explains the checks performed and how parameters affect behavior. However, it does not describe the output format or return values, which would enhance completeness.

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, so the description must compensate. It does so effectively with an 'Args:' section explaining each parameter's purpose and dependencies (e.g., model_path enables adhesion analysis, material is passed to that analysis). This adds crucial meaning beyond the schema's type-only definitions.

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 it performs a 'single-shot health assessment' of the current print, distinguishing it from 'watch_print' which starts a background thread. It lists specific checks (connectivity, temperature, progress, error state), making the purpose specific and unambiguous.

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 explicitly contrasts this tool with 'watch_print', indicating when to use a quick check versus persistent monitoring. It states it is for 'quick is the print OK right now? queries' without starting background tasks. However, it does not explicitly mention when not to use it or list all alternatives.

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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