Check whether the LMatch object is well-trained. 检查当前模板匹配的功能对象是否已训练。 Return True if it's trained, otherwise, return False. 若已训练，返回 true，否则返回 false。 布尔值(bool)类型 已训练，返回 true，否则返回 fals
AI agents call pat_match_is_learnt to retrieve information from Leaper Vision Toolkit without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
matchClassObjDescriptionJson | string | — | 模板匹配的功能对象用于训练模板匹配的功能。如果用户没有指定模板匹配的功能对象，请创建一个模板匹配的功能对象后传入。 如果用户指定模板匹配的功能对象，传入一个序列化的JSON字符串，属性包括：LpvClassName(调用工具函数的名称) 和 InputParameterFile(调用工具函数需要传入的参数文件名称)。 |
Parameters from the server's own tool schema.
This tool performs a check operation that queries the training status of a pattern matching object. It has no side effects, does not modify data, does not execute external operations, and does not delete or create resources. It is purely informational, making it a Read category tool with low severity since misuse would only expose internal state information.
From the tool's definition Tool name 'pat_match_is_learnt' and description indicate it 'Check whether the LMatch object is well-trained' and 'Return True if it's trained, otherwise, return False.' This is a query/inspection operation that retrieves state information without modifying…
Attacks that exploit this kind of access
Check whether the LMatch object is well-trained. 检查当前模板匹配的功能对象是否已训练。 Return True if it's trained, otherwise, return False. 若已训练，返回 true，否则返回 false。 布尔值(bool)类型 已训练，返回 true，否则返回 fals. It is categorised as a Read tool in the Leaper Vision Toolkit MCP Server, which means it retrieves data without modifying state.
pat_match_is_learnt accepts 1 parameter: matchClassObjDescriptionJson. The full parameter table on this page comes from the server's own tool schema.
Register the Leaper Vision Toolkit MCP server in PolicyLayer and add a rule for pat_match_is_learnt: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Leaper Vision Toolkit. Nothing to install.
pat_match_is_learnt is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the pat_match_is_learnt rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for pat_match_is_learnt. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
pat_match_is_learnt is provided by the Leaper Vision Toolkit MCP server (leaper-mcp/leaper-mcp-proxy). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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