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nickweedon

Skeleton MCP Server

by nickweedon

health_check

Verify the operational status and configuration of the MCP server to ensure it's running correctly and identify any issues.

Instructions

Check the health status of the MCP server.

Returns: A dictionary with the server status and configuration info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The health_check tool handler function, which performs a simple health check by returning server status and configuration info. It is registered using the @mcp.tool() decorator.
    @mcp.tool()
    async def health_check() -> dict[str, Any]:
        """
        Check the health status of the MCP server.
    
        Returns:
            A dictionary with the server status and configuration info.
        """
        config = get_client_config()
        return {
            "status": "healthy",
            "server": "Skeleton MCP Server",
            "version": "0.1.0",
            "api_configured": config.get("api_key") is not None,
        }
Behavior2/5

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

With no annotations provided, the description carries full burden. It states the tool returns a dictionary with server status and configuration info, which is helpful, but lacks details on behavioral traits such as whether it's safe for frequent use, if it requires authentication, or potential rate limits. This is inadequate for a tool with no annotation coverage.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded, with the first sentence stating the purpose clearly. The second sentence adds value by describing the return format. There's no wasted text, though it could be slightly more structured for optimal readability.

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?

Given the tool's low complexity (0 parameters) and the presence of an output schema, the description is minimally adequate. It explains what the tool does and hints at the return value, but lacks context on usage scenarios or behavioral details, making it incomplete for full agent guidance without additional information.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description correctly doesn't discuss parameters, and the baseline for 0 parameters is 4, as it avoids unnecessary information while being complete for this case.

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 clearly states the tool's purpose: 'Check the health status of the MCP server.' It specifies the verb ('Check') and resource ('health status of the MCP server'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_item' or 'list_items', which prevents a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios like server monitoring, debugging, or prerequisites, nor does it contrast with siblings like 'get_item' for data retrieval. This leaves the agent without context for tool selection.

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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