salome-mcp

by gnshb

Overview Schema Source Related Servers Discussions Admin

Python

Local

explode_shape

Split a GEOM object into subshapes (e.g., faces) and optionally add them to the SALOME study for further use.

Instructions

Explode GEOM object to subshapes and optionally add them to study.

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": {
      "shape_ref": "<shape_ref>"
    },
    "name": "explode_shape"
  }
}

Input Schema

Name	Required	Default
`shape_ref`	Yes
`add_to_study`	No
`result_prefix`	No	Exploded
`subshape_type`	No	FACE
`sorted_centres`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 1, 2026

TDQS

C2.6/5.0

Behavior2/5

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

With no annotations, the description carries the full burden of disclosing side effects. It mentions adding subshapes to the study but does not state whether the original object is modified, whether new objects are created permanently, or what happens with different subshape_type values. This leaves significant behavioral ambiguity.

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 description is a single, concise sentence with no filler or redundancy, making it easy to parse. However, it is arguably too terse, omitting necessary details, but this overconciseness is better captured by completeness rather than conciseness.

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?

The tool has five parameters, no annotations, and an output schema that is not described in the text. The description leaves numerous questions unanswered, such as naming conventions via result_prefix, allowed subshape types, and the effect of sorted_centres, making it inadequate for the tool's complexity.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate for the five parameters, but it only hints at 'add them to study' for add_to_study. It does not explain result_prefix, subshape_type (e.g., valid values like FACE, EDGE), or sorted_centres, leaving the agent unable to correctly set these parameters.

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 description uses the specific verb 'Explode' and identifies the resource as 'GEOM object' and the output as 'subshapes', clearly stating the core function. However, it does not explicitly distinguish this from sibling tools like list_subshapes, which also deal with subshapes, so it is clear but not fully differentiating.

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 description provides no guidance on when to use explode_shape versus alternatives such as list_subshapes, nor does it mention prerequisites like having a valid GEOM object. The only hint is 'optionally add them to study,' which implies a choice but does not specify appropriate use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.