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Kanysh Basic

Kanysh Basic

by almukhanomr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

dataset_validate

Validates a project dataset revision by artifact ID to check geological model data for issues before analysis, scenarios, or reports.

Instructions

dataset_validate

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": "dataset_validate"
  }
}

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

D1.6/5.0
Behavior2/5

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

Annotations carry the whole behavioral profile (readOnlyHint=false, idempotentHint=false, destructiveHint=false, openWorldHint=false), but the description adds nothing to them. It notably fails to explain why a 'validate' operation is flagged non-read-only and non-idempotent — e.g. whether it records/persists validation state or can produce different results on repeat calls — which is exactly the context an agent needs here. No contradiction, but zero value added.

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?

A single word is technically brief but this is under-specification rather than conciseness. There is no front-loaded statement of purpose or scope to anchor the reader.

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 mutation-flagged tool with a nested argument object, no output schema, and many similarly named siblings, the description provides no information at all. An agent would have to guess at what success/failure means and when this tool is the right call.

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?

There is a single nested 'request' parameter with artifact ref {id, revision} and project_id, documented at 100% coverage in the schema, so the schema does the heavy lifting. Per the high-coverage baseline this is a 3, but the description contributes nothing — the schema titles ('InspectArguments', 'Inspect') even suggest an inspection tool rather than validation, and the description does nothing to resolve that.

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?

No when-to-use, when-not-to-use, prerequisites, or named alternatives are given. An agent cannot distinguish dataset_validate from plan_validate, result_validate, workflow_validate, or simulation_validate on the basis of this text.

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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