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record_hardware_outcome

Log how embedded hardware fit after a print by recording result, fit, and notes to track outcomes and improve future designs.

Instructions

Record how a piece of hardware in a printed part came out (Pro).

Everything in Free, plus calibration that learns your printer, mid-print edits, and unlimited textures and decorations. Requires Kiln Pro. Upgrade: https://kiln3d.com/pricing?src=agent&tool=record_hardware_outcome

Input Schema

NameRequiredDescriptionDefault
fitNoDefault: "".
howNoDefault: "after_print".
stopNo
entryNoDefault: "".
gradeNoDefault: "".
layerNo
notesNoDefault: "".
resultYes
seat_idNoDefault: "".
cover_mmNo
hardwareYes
materialNoDefault: "".
design_idNoDefault: "".
predictedNoDefault: "".
printer_idNoDefault: "".
version_idNoDefault: "".
environmentNoDefault: "".
printer_modelNoDefault: "".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

C2.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses only the Pro-tier gate. For a write tool it says nothing about validation of `hardware`/`result`, whether records are immutable, what side effects occur, or whether the call can fail on missing design/printer context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three of four sentences are product marketing and an upgrade URL with tracking parameters ('?src=agent&tool=record_hardware_outcome'). This is agent-facing bloat that consumes attention without conveying invocation information.

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

Completeness2/5

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

An 18-parameter mutation tool with no annotations and no output schema needs a substantially richer description; this one covers only the tier requirement and a sales pitch. An agent cannot confidently determine required inputs beyond the schema's two required fields or predict the call's behavior.

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

Parameters2/5

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

Eighteen parameters with 72% schema description coverage, and the description contributes zero parameter meaning — nothing about what `result`, `fit`, `grade`, `predicted`, or `how` should contain. With coverage below the 80% threshold, the description is expected to compensate and instead adds nothing.

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

Purpose3/5

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

The first line does name a verb and resource: 'Record how a piece of hardware in a printed part came out.' That is a recognizable purpose, but 'came out' is colloquial and the definition never distinguishes this from the many near-identical siblings (record_hardware_insertion, record_print_outcome, record_magnet_outcome, record_load_outcome). An agent must guess which outcome-recording tool applies.

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 only usable guidance is the prerequisite 'Requires Kiln Pro.' There is no statement of when to call this versus record_hardware_insertion or any other outcome recorder, and no mention of preconditions, timing, or what data must exist first. The remaining text is a tier/upgrade pitch, not usage 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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