canvas_eval
Execute JavaScript code in the canvas context.
This record as markdown: /tools/cowork-os/canvas-eval.md
What canvas_eval does on CoWork OS
AI agents invoke canvas_eval to trigger actions in CoWork OS. 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 canvas_eval is rated High
This tool executes arbitrary JavaScript code in a canvas rendering context. While scoped to canvas operations rather than system-level commands, JavaScript execution in a browser/rendering context can access sensitive data, modify DOM elements, exfiltrate information, or trigger side effects depending on the canvas environment's capabilities and permissions.
From the tool's definition Tool name 'canvas_eval' and description 'Execute JavaScript code in the canvas context' explicitly indicates code execution capability.
Attacks that exploit this kind of access
The rule that runs canvas_eval safely
PolicyLayer is an MCP gateway: it sits between your AI agents and CoWork OS, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For canvas_eval, this is the rule to start with:
canvas_eval 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 CoWork OS, apply this rule, and every canvas_eval call is checked against it from then on.
Questions about canvas_eval
Execute JavaScript code in the canvas context. It is categorised as a Execute tool in the CoWork OS MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the CoWork OS MCP server in PolicyLayer and add a rule for canvas_eval: 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 CoWork OS. Nothing to install.
canvas_eval 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 canvas_eval 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 canvas_eval. 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.
canvas_eval is provided by the CoWork OS MCP server (CoWork-OS/CoWork-OS). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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