Skip to main content
Glama

monitor_print_vision

Captures webcam snapshot of a 3D print, analyzes it for visual failures, and returns structured metadata with optional auto-pause on issue detection.

Instructions

Snapshot + structured data for AI visual inspection of an in-progress print.

        Use when analyzing camera images for print failures. Returns webcam image
        (base64 or saved file) alongside structured metadata (temps, progress,
        phase, cost estimate, failure hints). Can auto-pause on detected issues.
        For a quick text status report, use ``monitor_print`` instead.
        For persistent background monitoring, use ``watch_print``.

        Args:
            printer_name: Target printer.  Omit for the default printer.
            include_snapshot: Whether to capture a webcam snapshot (default True).
            save_snapshot: Optional path to save the snapshot image.
            failure_type: Optional detected failure type (e.g. "spaghetti",
                "layer_shift", "warping").  Reported by the agent after visual
                inspection of a previous snapshot.
            failure_confidence: Confidence score (0.0-1.0) of the failure detection.
            auto_pause: If True, automatically pause the print when a failure is
                detected with confidence >= 0.8.  Defaults to the value of the
                ``KILN_VISION_AUTO_PAUSE`` environment variable (default False).
        

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
auto_pauseNo
failure_typeNo
printer_nameNo
save_snapshotNo
include_snapshotNo
failure_confidenceNo
Behavior5/5

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

No annotations are provided, so the description carries full burden. It discloses key behavioral traits: returns a webcam image (base64 or saved file) alongside structured metadata (temps, progress, phase, cost estimate, failure hints) and can auto-pause on detected issues. This is comprehensive for transparency.

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?

The description is well-structured with a summary, usage pointers, and parameter list. It is slightly lengthy but every sentence adds value. Minor redundancy could be trimmed, but overall efficient.

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 annotations, and no output schema, the description covers all necessary aspects: purpose, usage, parameter semantics, behavioral traits, and expected return values. An agent can confidently select and invoke this tool.

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%, meaning the description must compensate. It provides detailed explanations for all 6 parameters, including defaults (e.g., include_snapshot default True) and context (e.g., auto_pause defaults to an environment variable). This fully adds 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?

The description clearly states the tool's purpose: 'Snapshot + structured data for AI visual inspection of an in-progress print.' It contrasts with sibling tools by directing to 'monitor_print' for text status and 'watch_print' for persistent monitoring, thus distinguishing itself effectively.

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 states when to use the tool: 'Use when analyzing camera images for print failures.' It also provides explicit alternatives for related tasks, such as 'monitor_print' for a quick text status and 'watch_print' for persistent background monitoring, offering clear usage boundaries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/codeofaxel/kiln'

If you have feedback or need assistance with the MCP directory API, please join our Discord server