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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

suggest_spool_swaps

Read-only

Suggests minimal spool swaps to complete all queued jobs by comparing required materials with loaded spools and indicating which shelf spools to load and where, including across multiple machines.

Instructions

Suggest minimal spool swaps to run all queued jobs.

        Compares what the jobs need with what is loaded and says which
        shelf spools to load, and where.  On one machine it answers for
        that machine; across several machines it plans the fewest
        physical spool changes between them (Kiln Business).

        Args:
            jobs: List of job dicts with ``material_type`` and ``required_grams``.

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": {
      "jobs": "<jobs>"
    },
    "name": "suggest_spool_swaps"
  }
}

Input Schema

NameRequiredDescriptionDefault
jobsYesList of job dicts with ``material_type`` and ``required_grams``.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.5.1
    • addedInput schema / properties / jobs / description
      Added value: +"List of job dicts with ``material_type`` and ``required_grams``."
  2. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description still adds real context beyond them: it explains the comparison it performs, that output is a load plan naming shelf spools and positions, and that cross-machine minimal-change planning is gated behind the Kiln Business tier — a licensing constraint an agent could not otherwise know.

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 core capability and the machine-scope distinction are front-loaded in two short sentences with no filler. The trailing docstring-style 'Args:' block is redundant against a 100%-covered schema and the hard-wrapped indentation is slightly noisy, but the whole thing is short and skimmable.

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?

With no output schema, the description does describe the return content (which spools to load and where) and notes the tier requirement and scope switch, which covers most of what an agent needs. Minor gaps remain: it does not say whether spools currently mounted or in use by an active print are considered, nor what happens when jobs cannot be satisfied with available spools.

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?

There is only one parameter and schema description coverage is 100%; the description's Args block repeats the schema text verbatim ('List of job dicts with material_type and required_grams'), adding no extra meaning. Baseline 3 applies since the schema carries the semantics. It could have added value by clarifying whether jobs must be from the queue, whether other keys are honoured, or how required_grams is interpreted.

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?

The first sentence gives a specific verb and resource: 'Suggest minimal spool swaps to run all queued jobs', and the second clarifies the comparison it performs (needed vs. loaded) and the output ('which shelf spools to load, and where'). It also distinguishes single-machine from multi-machine behaviour. It does not name or contrast any sibling (e.g. plan_fleet_material_change, list_spools, get_restock_suggestions), so an agent must infer the boundary itself.

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?

Usage is implied rather than stated: the tool is for planning spool changes before running queued jobs, and the multi-machine mode is tied to Kiln Business. There is no explicit 'use this when…' / 'do not use this when…' and no pointer to alternative tools for related questions such as material sufficiency or fleet assignment.

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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