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cloudsmithy

Easysearch MCP Server

by cloudsmithy

cat_thread_pool

Monitor thread pool performance in Easysearch clusters by retrieving active thread counts, queue sizes, and rejection metrics for search, write, and get operations.

Instructions

    获取线程池状态
    
    参数:
        thread_pool: 线程池名称(可选)如 search/write/get
    
    返回各线程池的活跃线程数、队列大小、拒绝数
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thread_poolNo
Behavior2/5

Does 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 returns '活跃线程数、队列大小、拒绝数' (active thread count, queue size, rejection count), which gives some output context, but doesn't describe whether this is a read-only operation, its performance impact, error conditions, or authentication needs. For a monitoring tool with zero annotation coverage, this leaves significant behavioral gaps.

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 concise with three clear sections: purpose statement, parameter explanation, and return value description. Each sentence earns its place by adding specific information. The structure is logical and front-loaded with the main purpose. Minor formatting issues (extra whitespace) don't detract significantly from clarity.

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 moderate complexity (monitoring with one optional parameter), no annotations, and no output schema, the description is minimally adequate. It covers the purpose, parameter meaning, and return values, but lacks behavioral context like safety, performance, or error handling. The return value description helps compensate for the missing output schema, but overall completeness is limited to basic operational understanding.

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 description adds meaningful parameter information beyond the schema. The schema has 0% description coverage and only shows 'thread_pool' as an optional string parameter. The description explains this is '线程池名称(可选)如 search/write/get' (thread pool name, optional, e.g., search/write/get), providing examples and clarifying it's optional. With only one parameter and good semantic clarification, this compensates well for the schema's lack of descriptions.

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: '获取线程池状态' (get thread pool status). It specifies the verb '获取' (get) and resource '线程池状态' (thread pool status), making it unambiguous what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'cat_nodes' or 'cat_health' which also provide monitoring information, though the specific focus on thread pools is implied.

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 any prerequisites, context for usage, or comparisons to sibling tools like 'nodes_stats' or 'cluster_stats' that might also provide thread pool information. The agent must infer usage solely from the purpose statement.

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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