Trace pixel-space features from a reference photo into normalized [0..1] waypoints the agent can map to mm via a known scale anchor and feed to path().spline / path().nurbsSegment. Three backends are dispatched behind the scenes: opencv (deterministic; uniform-bg silhouette only), vision-llm (Cla...
Part of the Kernelcad server.
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AI agents invoke trace_from_image to trigger processes or run actions in Kernelcad. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
trace_from_image can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"trace_from_image": {
"limits": [
{
"counter": "trace_from_image_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Kernelcad policy for all 48 tools.
These attack patterns abuse exactly the kind of access trace_from_image gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Trace pixel-space features from a reference photo into normalized [0..1] waypoints the agent can map to mm via a known scale anchor and feed to path().spline / path().nurbsSegment. Three backends are dispatched behind the scenes: opencv (deterministic; uniform-bg silhouette only), vision-llm (Claude vision; named points/cluttered backgrounds; caller-supplied ANTHROPIC_API_KEY), and hybrid (opencv silhouette + LLM-labeled named points). Default backend is auto — the tool picks based on the image's corner-color stddev. Accuracy honesty: opencv contour is geometrically exact; vision-LLM is typically 5–10% off on dense landmarks. Per-feature confidence is reported. Caller pays for any vision-LLM API spend via their own ANTHROPIC_API_KEY. Pair with the kernelcad-trace-from-image skill for the conversion-to-mm pipeline.. It is categorised as a Execute tool in the Kernelcad MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Kernelcad MCP server in PolicyLayer and add a rule for trace_from_image: 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 Kernelcad. Nothing to install.
trace_from_image is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the trace_from_image 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 trace_from_image. 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.
trace_from_image is provided by the Kernelcad MCP server (kernelcad). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 48 Kernelcad tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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