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get_validation_help

Read-only

Get guidance on common validation issues, proper syntax, and best practices for creating valid Ilograph diagrams.

Instructions

    Provides comprehensive help for Ilograph diagram validation.

    Returns guidance on common validation issues, proper syntax,
    and best practices for creating valid Ilograph diagrams.

    Returns:
        str: Detailed validation help in markdown format
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'get_validation_help' tool. It returns a comprehensive markdown-formatted guide on Ilograph diagram validation, including common issues, solutions, and examples. Registered via @mcp.tool() decorator with metadata.
        @mcp.tool(
            annotations={
                "title": "Get Validation Help",
                "readOnlyHint": True,
                "description": "Provides guidance on Ilograph diagram validation and common issues",
            }
        )
        async def get_validation_help(ctx: Context) -> str:
            """
            Provides comprehensive help for Ilograph diagram validation.
    
            Returns guidance on common validation issues, proper syntax,
            and best practices for creating valid Ilograph diagrams.
    
            Returns:
                str: Detailed validation help in markdown format
            """
            try:
                await ctx.info("Providing Ilograph validation help")
    
                help_content = """# Ilograph Diagram Validation Help
    
    ## Overview
    This validation tool checks your Ilograph diagrams for both YAML syntax correctness and Ilograph-specific schema compliance.
    
    ## Validation Process
    1. **YAML Syntax Check**: Ensures your diagram is valid YAML
    2. **Schema Validation**: Checks Ilograph-specific structure and properties
    3. **Best Practice Suggestions**: Provides recommendations for improvement
    
    ## Common Issues and Solutions
    
    ### YAML Syntax Errors
    - **Indentation**: Use consistent spaces (2 or 4), not tabs
    - **Missing Colons**: Properties need colons (`name: value`)
    - **List Format**: Use dashes for lists or bracket notation
    - **Quoted Strings**: Quote strings with special characters
    
    ### Ilograph Schema Issues
    - **Missing Required Properties**: Resources need `name` or `id`
    - **Unknown Properties**: Check property names against specification
    - **Duplicate IDs**: Resource IDs must be unique
    - **Invalid Relations**: Relations need both `from` and `to`
    
    ## Valid Top-Level Properties
    - `resources`: Your diagram components (required for meaningful diagrams)
    - `perspectives`: Different views of your architecture
    - `contexts`: Multiple context views
    - `imports`: External namespace imports
    - `layout`: Diagram layout properties
    
    ## Example Valid Structure
    ```yaml
    imports:
    - from: ilograph/aws
      namespace: AWS
    
    resources:
    - name: Web Server
      subtitle: Frontend
      description: Serves the web application
      icon: server.svg
      children:
      - name: Load Balancer
        instanceOf: AWS::ElasticLoadBalancer
    
    perspectives:
    - name: System Overview
      relations:
      - from: User
        to: Web Server
        label: HTTPS requests
    ```
    
    ## Getting More Help
    - Use `fetch_spec_tool()` to get the complete Ilograph specification
    - Use `fetch_documentation_tool(section='tutorial')` for detailed tutorials
    - Use `fetch_example_tool()` to see working example diagrams
    
    ## Tips for Success
    1. Start with simple structures and build complexity gradually
    2. Use consistent naming conventions
    3. Add descriptions to improve documentation
    4. Validate frequently during development
    5. Check examples for pattern guidance
    """
    
                await ctx.info("Validation help provided successfully")
                return help_content
    
            except Exception as e:
                error_msg = f"Error providing validation help: {str(e)}"
                await ctx.error(error_msg)
                return f"Error: {error_msg}"
  • The call to register_validate_diagram_tool(mcp) in the server setup, which defines and registers the get_validation_help tool (along with validate_diagram_tool).
    register_validate_diagram_tool(mcp)
  • Tool name listed in get_tool_info() for reference.
    "get_validation_help",
  • Docstring defining the tool's purpose and return type (str). No input parameters required.
    """
    Provides comprehensive help for Ilograph diagram validation.
    
    Returns guidance on common validation issues, proper syntax,
    and best practices for creating valid Ilograph diagrams.
    
    Returns:
        str: Detailed validation help in markdown format
    """
Behavior4/5

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

Annotations declare readOnlyHint=true, and the description aligns by describing a read-only help function. It adds valuable behavioral context beyond annotations by specifying the return format ('Detailed validation help in markdown format') and content scope ('guidance on common validation issues, proper syntax, and best practices'), enhancing transparency without contradiction.

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 front-loaded with the core purpose, followed by specifics on return content and format, all in three concise sentences with zero waste. Each sentence earns its place by adding distinct value: purpose, content details, and output format.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters, read-only), annotations cover safety, and the description details return content and format, it is largely complete. However, without an output schema, it could slightly enhance completeness by specifying markdown structure or example output, but this is minor.

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?

With 0 parameters and 100% schema description coverage, the baseline is 4. The description compensates by clearly stating there are no inputs needed ('Provides comprehensive help' without mention of parameters), which aligns with the empty input schema and adds semantic clarity.

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?

The description clearly states the specific verb ('Provides comprehensive help') and resource ('for Ilograph diagram validation'), distinguishing it from sibling tools like 'validate_diagram_tool' (which validates) or 'fetch_example' (which retrieves examples). It precisely defines the tool's function without being tautological.

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?

The description implies usage context ('common validation issues, proper syntax, and best practices') but does not explicitly state when to use this tool versus alternatives like 'validate_diagram_tool' for actual validation or 'check_documentation_health' for documentation checks. It provides some guidance but lacks explicit comparisons or exclusions.

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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