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build123d-mcp

build123d-mcp

by pzfreo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

restore_snapshot

Idempotent

Revert to a previously saved snapshot of the 3D model geometry, restoring current_shape and show() objects to their earlier state.

Instructions

Restore geometric state from a previously saved snapshot (current_shape and the show() registry). The Python variable namespace is NOT restored — execute() calls made after the snapshot are still in scope, but current_shape and all show() objects revert to what they were at snapshot time. Raises an error if the snapshot name does not exist.

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": {
      "name": "<name>"
    },
    "name": "restore_snapshot"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.19
  2. Removedv0.3.17
  3. First observedv0.3.10

TDQS

A4.1/5.0
Behavior4/5

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

Annotations indicate idempotentHint=true, which the description supports by implying the operation is reversible and idempotent. Description adds nuance about what is not restored (Python namespace) and error behavior, exceeding annotation detail.

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

Conciseness5/5

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

Three sentences, front-loaded with purpose, followed by behavioral nuance and error condition. No superfluous words.

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?

For a simple tool with one parameter and output schema, the description covers main behavior, constraints, and error. Could add a note on idempotency but annotations cover it.

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?

Schema coverage is 0%, so description must compensate. The description only indirectly mentions the 'name' parameter by stating an error if snapshot name does not exist. It does not explain what valid names are, where snapshots come from, or format requirements.

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?

Description clearly states 'Restore geometric state from a previously saved snapshot' with specific details about what is restored (current_shape and show() registry). This is a specific verb and resource, differentiating from sibling tools.

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?

Description provides context on when to use: to revert geometric state while preserving variable namespace. It also mentions error on non-existent snapshot. However, it does not explicitly compare to alternatives like diff_snapshot.

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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