Retrieve statistics from the memory engine to review captured errors, reusable skills, and context retrieval patterns for system assessment.
获取记忆引擎的统计信息。
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": "get_stats"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only says 'get statistics' and does not explicitly state that it is a read-only operation, nor does it describe any side effects, persistence, or the structure of the returned data. While '获取' implies reading, it is not explicit, and nothing is disclosed about what the agent will receive.
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 a single short sentence with no unnecessary words. It is maximally concise and front-loaded, stating the action and resource immediately. No filler or repetition exists.
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?
For a tool with no output schema and no annotations, the description should explain what statistics are returned or at least hint at the format. It does not, leaving the agent to guess what the response will contain. The description is too sparse to be considered complete for a tool that has any meaningful output.
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 tool has zero parameters, so the baseline is 4 per the rubric. The schema is fully covered (empty), and the description adds nothing about parameters because none exist. This matches the baseline that requires no additional parameter documentation.
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 it retrieves statistics from the memory engine, using a specific verb ('获取' = get) and a distinct resource. It is distinguishable from sibling tools like search_memory or get_context because it focuses on statistics. However, it does not specify what kind of statistics, making it slightly vague but still clear on its core purpose.
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?
No guidance is provided on when to use this tool versus alternatives. The description only states the action without any context on typical use cases, prerequisites, or when it should not be used. Given the many sibling tools, an agent would have no direction on selecting this over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.