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Kanysh Basic

Kanysh Basic

by almukhanomr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

seismic_attribute

Computes RMS or envelope seismic attributes from a project volume artifact with a configurable sample window and local execution policy for subsurface model analysis.

Instructions

seismic_attribute

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": "seismic_attribute"
  }
}

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

D1.7/5.0
Behavior2/5

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

Annotations supply only the generic safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=false); the description adds nothing about job submission, async execution, or the idempotency_key behavior. Some credit is due because annotations at least establish that this is a non-destructive mutation run against a closed system, but the description itself contributes zero behavioral context.

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 only one word, so it is not verbose, but that brevity is under-specification rather than concision — there is no front-loaded purpose statement or structure. The single token conveys no information the name did not already convey.

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 is a nested, execution-policy-bearing job submission with no output schema, so the description carries real burden — what is produced, whether the call blocks or returns a job handle, how to poll it. The very rich input schema prevents a 1, but the description is effectively absent.

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 request object, volume {id, revision}, window, attribute enum, execution policy, project_id, and idempotency_key are all documented in the schema. The description adds no meaning beyond that, so the baseline of 3 applies.

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 when-to-use guidance, no prerequisites, and no mention of alternatives among the many seismic-related siblings. An agent has to infer entirely from the name and schema that this is a compute-job submission rather than an import, inspect, or slicing operation.

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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