Skip to main content
Glama
Sign In
Plant Simulation Research Bridge

Plant Simulation Research Bridge

by AmaneSuzuha000
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

validate_instance

Validate a scheduling instance to report engine compatibility and summary statistics before running experiments.

Instructions

Validate a scheduling instance and report engine compatibility and summary statistics.

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": {
      "instance": "<instance>"
    },
    "name": "validate_instance"
  }
}

Input Schema

NameRequiredDescriptionDefault
instanceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool validates the instance and reports engine compatibility and summary statistics, which gives useful behavioral context, but it does not state whether the operation is read-only, what happens on invalid input, or what errors may be returned.

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

Conciseness5/5

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

The description is a single efficient sentence with the action and reported outputs front-loaded. There is no redundant or filler wording.

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?

There is no output schema, so the description should explain return values more fully. It mentions engine compatibility and summary statistics but not their structure or meaning, and the ambiguous input parameter remains underspecified for a validation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the single parameter. It does not explain what "instance" should contain, whether it is an object or string in practice, or what fields are expected, leaving the input semantics largely undocumented.

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 uses a specific verb, "Validate," and a clear resource, "a scheduling instance," and adds that it reports engine compatibility and summary statistics. It does not explicitly name or distinguish itself from sibling tools, but the purpose is unambiguous.

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?

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no conditions under which validation should be skipped. The name implies a validation workflow, but the description provides no routing information.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools