pingVerify server connectivity by sending a ping request; receive a pong response to confirm the Shogi MCP Server is operational and ready for shogi analysis.
ヘルスチェック（常に pong を返す）
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "ping"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool always returns 'pong,' which implies a read-only, non-destructive operation, but it doesn't cover aspects like error handling, latency, or side effects. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single sentence in Japanese that directly states the tool's function. It's front-loaded with the key information ('health check') and avoids any redundant or verbose language, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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, no output schema, simple purpose), the description is adequate but minimal. It covers the basic purpose and behavior but lacks details on usage context or advanced behavioral traits. With no annotations or output schema, it meets the minimum viable standard but could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 information is needed. The description doesn't add any parameter details, which is appropriate. Baseline is 4 for 0 parameters, as it avoids unnecessary repetition and focuses on the tool's purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'ヘルスチェック（常に pong を返す）' translates to 'Health check (always returns pong).' This specifies the verb ('health check') and the resource/outcome ('always returns pong'), making it distinct from siblings like 'analyze' or 'eval_at.' However, it doesn't explicitly differentiate from potential similar tools (e.g., 'status' or 'health'), so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 system monitoring, connectivity testing, or prerequisites. Without any usage context, the agent must infer from the purpose alone, which is insufficient for optimal tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.