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srunx

srunx

by ksterx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

validate_workflow

Checks workflow YAML files for syntax errors, structural correctness, dependency resolution, and circular dependencies to ensure valid workflow definitions.

Instructions

Validate a workflow YAML file for correctness.

Checks for valid YAML syntax, correct job structure, dependency resolution,
and circular dependency detection.

Args:
    yaml_path: Path to the YAML workflow file to 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": {
      "yaml_path": "<yaml_path>"
    },
    "name": "validate_workflow"
  }
}

Input Schema

NameRequiredDescriptionDefault
yaml_pathYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.0.3
  2. Removedv3.0.2
  3. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses the validation checks performed, but does not describe output format or side effects. Output schema exists but description could add context on return values.

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?

Description is concise (two paragraphs, 4 lines) with front-loaded purpose. No redundant information.

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?

Tool is simple with one parameter and output schema exists, but description does not explain what the output looks like (e.g., success/failure, error details). This gap reduces completeness despite schema coverage.

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

Parameters4/5

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

Schema description coverage is 0%, so description must compensate. It provides a clear parameter description: 'Path to the YAML workflow file to validate'. This adds meaningful context beyond the schema's type-only definition.

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

Purpose5/5

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

Description clearly states the tool validates a workflow YAML file for correctness, listing specific checks (YAML syntax, job structure, dependency resolution, circular dependency detection). This distinguishes it from siblings like run_workflow or create_workflow.

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

Usage Guidelines3/5

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

Usage is implied (before running a workflow) but no explicit guidance on when to use vs alternatives like run_workflow or create_workflow. No exclusions or prerequisites mentioned.

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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