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orcaslicer-mcp

orcaslicer-mcp

by MaxEllis
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

List print history

list_print_history
Idempotent

Lists recent Klipper print outcomes against slicer time estimates, including result, duration, filament use, and failure reasons, and stores them for later model recall.

Instructions

List how recent prints on the printer ended against the slicer's estimates (Klipper only); recall_prints looks up one model's past prints.

For each finished job: result (success, cancelled or error), how long it took against the slicer's estimate, filament used, and for failed or stopped jobs the printer's own reason while its console still holds it. summary says how the slicer's time estimates compare with reality once there are a few finished prints. Also copies those jobs into the local outcome store (safe to repeat), so recall_prints can learn from them. Klipper printers only. limit is capped at 50.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_print_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.17

TDQS

A4.3/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing the write side effect that explains readOnlyHint=false: jobs are copied into a local outcome store, and that write is 'safe to repeat', which substantiates idempotentHint=true. It also discloses the limit cap of 50 and enumerates what each result row contains, so the agent knows both the mutation and the return shape.

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 routing distinction is front-loaded in the first clause, and each subsequent sentence adds a distinct fact (result fields, summary behavior, outcome-store copy, platform limit, limit cap). It runs long with some parenthetical asides, but little is wasted.

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 carries the return-shape burden and does so by naming the per-job fields and the `summary` field. Remaining gaps are minor: behavior on an empty history, error cases, and the precise meaning of `limit`.

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 coverage is 0% for the single `limit` parameter, so the description must compensate. It only supplies the cap ('limit is capped at 50'), leaving the default of 10 and the exact unit (number of jobs) implicit; that is partial compensation, not full.

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?

States a specific verb and resource ('List how recent prints on the printer ended') plus the comparison being made against slicer estimates, and explicitly contrasts with recall_prints ('looks up one model's past prints'). An agent can distinguish the two without opening either schema.

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

Usage Guidelines4/5

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

Names the alternative (recall_prints) and the scope difference, and gives a hard applicability constraint ('Klipper only'). It does not spell out a general when-not case beyond the platform restriction, but the routing guidance is clear enough to select correctly.

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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