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Kanysh Basic

Kanysh Basic

by almukhanomr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

properties_krige

Perform kriging interpolation of phi or permeability fields from well conditioning data and variogram settings within a specified zone and project.

Instructions

properties_krige

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_krige"
  }
}

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 this is a mutation (readOnlyHint=false, idempotentHint=false, destructiveHint=false), but the description adds nothing about what is created, whether existing properties are overwritten, or what the job/idempotency behavior is. All behavioral burden falls on the description here and it discloses none of it.

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?

It is extremely short, but this is under-specification rather than concision — the single token carries no information and is not front-loaded with any purpose. There is nothing to structure because nothing was written.

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?

For a tool with a deep nested request object (project ref, artifact revision, conditioning wells, variogram parameters, execution policy) and no output schema, the description is completely inadequate. An agent has no way to know what the call produces or how it fits into a geostatistical workflow.

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%: the nested request object fully documents field, zone_id, conditioning, variogram parameters, execution policy, and the idempotency key. The description adds no additional meaning, but the baseline of 3 applies because the schema does the work.

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 whatsoever on when to use this tool, when not to, or which sibling to choose instead. An agent could not infer prerequisites or routing from a bare identifier.

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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