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Kanysh Basic

Kanysh Basic

by almukhanomr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

model_build

Build a regular geological model for a project using GemPy or explicit horizontal layers, with configurable grid, fault, surface, orientation, and execution settings.

Instructions

Define a regular geological model: GemPy or explicitly horizontal layers.

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": {
      "request": "<request>"
    },
    "name": "model_build"
  }
}

Input Schema

NameRequiredDescriptionDefault
requestYesTool arguments object (all fields documented; Z is positive upward).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already disclose that the tool is not read-only, not destructive, not idempotent, and closed-world. The description adds method choices but no behavioral context beyond that, such as whether a model artifact or job is created, how idempotency behaves, or what execution side effects to expect.

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 front-loaded sentence with no wasted wording. It is concise and directly states the tool's purpose, though the method clause is terse rather than elaborative.

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?

The schema is very rich and the annotations cover the safety profile, so the minimal description is not fatal. However, for a complex model-building tool with method-dependent requirements, the description omits important context such as project requirement, method-specific artifacts, and execution/output implications.

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 the extensive nested field descriptions already explain project_id, grid, method, horizons_z, surfaces, orientations, execution, and idempotency_key. The description only adds high-level method names and does not go beyond the schema.

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 states a specific verb and resource: define a regular geological model, with the two supported structural methods named. It is clear what the tool does, though it does not explicitly differentiate itself from sibling model-related tools such as model_qc or model_diff.

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 names GemPy and explicitly horizontal layers but gives no guidance on when to choose one method over the other. There is no mention of prerequisites, alternatives, or when this tool should be used instead of adjacent model or workflow tools.

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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