sandbox_stop
Stop the user's session sandbox gracefully (state → 'ending'; queued work drains). Frees nothing to re-spend — the day's allowance was spent at start — but a stopped sandbox is good hygiene when the work is done.
This record as markdown: /tools/ai-rokha-rokha/sandbox-stop.md
What sandbox_stop does on Rokha
AI agents invoke sandbox_stop to trigger actions in Rokha. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
wallet_address | string | Yes |
Parameters from the server's own tool schema.
Why sandbox_stop is rated High
Triggers external operation (sandbox termination) with irreversible session state changes and potential disruption.
From the tool's definition Stop the user's session sandbox gracefully; state transition and work draining.
Attacks that exploit this kind of access
The rule that runs sandbox_stop safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Rokha, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For sandbox_stop, this is the rule to start with:
sandbox_stop 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 Rokha, apply this rule, and every sandbox_stop call is checked against it from then on.
Questions about sandbox_stop
Stop the user's session sandbox gracefully (state → 'ending'; queued work drains). Frees nothing to re-spend — the day's allowance was spent at start — but a stopped sandbox is good hygiene when the work is done. It is categorised as a Execute tool in the Rokha MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
sandbox_stop accepts 1 parameter: wallet_address. Required: wallet_address. The full parameter table on this page comes from the server's own tool schema.
Register the Rokha MCP server in PolicyLayer and add a rule for sandbox_stop: 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 Rokha. Nothing to install.
sandbox_stop 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 sandbox_stop 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 sandbox_stop. 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.
sandbox_stop is provided by the Rokha MCP server (https://rokha.ai/mcp/jsonrpc). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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