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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

get_calibration_freshness

Read-only

Check calibration freshness for all combinations on a printer, with an optional material filter, to see which calibrations need review.

Instructions

Report freshness for every calibration combination of a printer.

Needs Kiln Pro.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "printer_id": "<printer_id>"
    },
    "name": "get_calibration_freshness"
  }
}

Input Schema

NameRequiredDescriptionDefault
materialNooptional filter. When empty, every material for the printer is included. Default: "".
printer_idYesThe printer whose calibration freshness is reported, the key its profile is kept under.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.5.1
    • changedInput schema / properties / material / description
      Previous value: -"Default: \"\"."New value: +"optional filter.  When empty, every material for the printer is included. Default: \"\"."
    • addedInput schema / properties / printer_id / description
      Added value: +"The printer whose calibration freshness is reported, the key its profile is kept under."
  2. Addedv1.5.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds one piece of context beyond that — the Kiln Pro entitlement requirement — but says nothing about what 'freshness' means (thresholds, stale vs. current states) or how the report is structured, which matters for a read tool with no output schema.

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?

Two short sentences with the core action front-loaded and the entitlement constraint separated onto its own line, so nothing is buried. It is efficient but borders on under-specification for a domain concept ('freshness') the agent must interpret.

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?

For a simple, non-destructive two-parameter read tool with full schema coverage and clear annotations, the description covers the essentials. The notable gap is the absence of an output schema combined with no description of what a freshness report contains, leaving the agent to guess at the return shape.

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 100%, so both parameters (printer_id, material filter) are already documented with defaults and empty-string behavior. The description's phrase 'every calibration combination of a printer' only loosely reinforces the unfiltered-by-material default and adds no new syntax or format detail. Baseline 3 applies.

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?

States a specific verb and object — 'Report freshness for every calibration combination of a printer' — which is concrete enough for an agent to know it retrieves calibration staleness data rather than performing calibration. It does not name any sibling (e.g. assess_calibration_status, classify_calibration_confidence, get_calibration_health_recommendations), so the boundary with those closely related tools is left implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Needs Kiln Pro' gives an eligibility prerequisite, which is genuine usage guidance. However, there is no statement of when an agent should pick this over the other calibration tools in the sibling list, nor any exclusion such as 'use assess_calibration_status for overall health'.

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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