设置图像滤波工具的Sigma值和Gain值。 Change the kernel using the specified sigma and gain value. Sigma controls the filter kernel's smoothness, gain controls the overall strength of the sharpening effect. 返回结构是一个序列化的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)。这两个属性的值可以从前处理的MCP...
AI agents use il_image_filter_set_kernel_sigma to create or update resources in Leaper Vision Toolkit — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Leaper Vision Toolkit environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
kGain | number | — | 锐化强度,传入类型为double类型，默认值为1.0，对于 Sharpen()，kGain 用于控制锐化效果的强度。 |
kSigma | number | — | 滤波核的平滑程度，传入类型为double类型，对于 HighPass()，Gaussian() 和 Sharpen() 方法，若设置为 0（默认），则由核尺寸自动计算为：1/6。 若核尺寸设置为 0，则由 Sigma 值自动计算合适的核尺寸，约为 6 × kSigma。 对于 EdgePreserveDenoise |
InputParameterFile | string | — | 指定的 ILImageFilter 类的文件地址，调用工具函数需要传入的参数文件名称。在调用此工具前要保证前处理中一定要有且仅有一次的 ILImageFilter 初始化工具调用。这个属性的值需要从前处理的MCP工具的返回值 InputParameterFile 字段中获取。 |
Parameters from the server's own tool schema.
The tool modifies filter configuration (sigma and gain values) which changes how images are processed, making it a Write operation that alters processing parameters. It does not execute arbitrary code or delete data, so Write is most appropriate. Severity is medium because misconfiguration could produce undesired image outputs, but the effects are reversible by resetting parameters.
From the tool's definition Tool modifies image filter parameters: 'Change the kernel using the specified sigma and gain value. Sigma controls the filter kernel's smoothness, gain controls the overall strength of the sharpening effect.' This adjusts filter settings that affect image…
Attacks that exploit this kind of access
设置图像滤波工具的Sigma值和Gain值。 Change the kernel using the specified sigma and gain value. Sigma controls the filter kernel's smoothness, gain controls the overall strength of the sharpening effect. 返回结构是一个序列化的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)。这两个属性的值可以从前处理的MCP工具的返回值中获取。LpvClassName 表示图像滤波工具的功能调用的对象名称，目前名称应为：ILImageFilter。 InputParameterFile 表示图像滤波工具的功能调用的对象的参数文件名称。. It is categorised as a Write tool in the Leaper Vision Toolkit MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
il_image_filter_set_kernel_sigma accepts 3 parameters: kGain, kSigma, InputParameterFile. 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 il_image_filter_set_kernel_sigma: 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.
il_image_filter_set_kernel_sigma is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the il_image_filter_set_kernel_sigma 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 il_image_filter_set_kernel_sigma. 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.
il_image_filter_set_kernel_sigma 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.
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