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analyze_print_file

Read G-code file headers on the printer to extract slicer metadata like material, print time, temperatures, and filament usage. Useful when filenames lack meaning.

Instructions

Analyze a G-code file on the printer and extract its metadata.

Reads the file header to extract slicer-embedded metadata such as
material type, estimated print time, temperatures, layer height,
and filament usage.  This is especially useful when filenames are
meaningless (e.g. ``test5112.gcode``) and the agent needs to
understand what a file will print.

.. note::
    For multi-object .gcode.3mf files, also consider using
    ``list_plate_objects()`` to see individual objects on the plate.

Args:
    filename: Name or path of the file as shown by ``printer_files()``.

Returns a JSON object with:
- ``filename``: the file name
- ``metadata``: extracted metadata (material, time, temps, slicer, etc.)
- ``has_metadata``: whether any metadata was found

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filenameYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It explains it reads the file header (non-destructive) and lists the metadata extracted. However, it does not explicitly state that the operation is read-only or mention potential side effects.

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 concise, well-structured with a note, and front-loaded. Every sentence adds value without waste.

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?

The description is quite complete for a simple tool: purpose, usage context, input format, and return structure. It could mention error cases or prerequisites, but overall sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% coverage, but the description adds meaning by specifying the filename is as shown by 'printer_files()'. This helps the agent locate the correct file.

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 analyzes a G-code file and extracts metadata. It specifies the verb 'analyze' and resource 'G-code file', and distinguishes from siblings like 'printer_files' and 'list_plate_objects'.

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 when to use: 'when filenames are meaningless' and recommends an alternative tool ('list_plate_objects') for multi-object files. This provides clear 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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