This record as markdown: /tools/kiln/run-calibrate.md
What run_calibrate does on Kiln
AI agents invoke run_calibrate to trigger actions in Kiln. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why run_calibrate is rated High
The tool triggers execution of calibration procedures on 3D printers, which constitute external operations with effects dependent on printer state and configuration. While not destructive (calibration is reversible) or financial, it executes commands that affect physical device behavior.
From the tool's definition Tool name 'run_calibrate' and context of 3D printer control via OctoPrint, Moonraker, Bambu, Prusa, Elegoo platforms indicates execution of calibration routines on physical hardware.
Attacks that exploit this kind of access
The rule that runs run_calibrate safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Kiln, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For run_calibrate, this is the rule to start with:
run_calibrate stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Kiln, apply this rule, and every run_calibrate call is checked against it from then on.
Questions about run_calibrate
run_calibrate is a execute tool on the Kiln MCP server. It is categorised as a Execute tool in the Kiln MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Kiln MCP server in PolicyLayer and add a rule for run_calibrate: 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 Kiln. Nothing to install.
run_calibrate 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 run_calibrate 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 run_calibrate. 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.
run_calibrate is provided by the Kiln MCP server (codeofaxel/Kiln). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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