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Kanysh Basic

Kanysh Basic

by almukhanomr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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properties_assign

Assign zone properties (porosity, net-to-gross, water saturation, permeability) to a geological model using project and model revision, preparing it for simulation.

Instructions

properties_assign

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": "properties_assign"
  }
}

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

D1.4/5.0
Behavior1/5

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

Annotations declare readOnlyHint=false, destructiveHint=false, and idempotentHint=false, but the description adds no behavioral context at all. It does not say whether this mutates an existing model revision, creates a new artifact, or how the idempotency_key interacts with the non-idempotent annotation — a point worth clarifying.

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

Conciseness2/5

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

The single word is technically concise but represents under-specification rather than concision. There is no front-loaded statement of what the tool does or what it returns.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a complex mutation tool with a deeply nested request object (model ref, zone property map, execution policy), no output schema, and no description to explain the assignment semantics or expected outcome. The definition is wholly inadequate for an agent to invoke it confidently.

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%, with rich nested documentation for request.project_id, request.model (id/revision), and request.zones. Per the high-coverage baseline, the schema carries the parameter semantics even though the description contributes nothing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tautological: description restates name/title.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus the many sibling property/model tools such as properties_krige, properties_simulate, or model_build. The agent must infer entirely from the name and schema.

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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