start_instance_loop
Give an agent an objective and let it work autonomously on the server. Durable: it survives you closing the browser, and its spend is bounded by a budget. Returns a run id — poll it with check_instance_loop.
This record as markdown: /tools/io-github-proagentstore-platform/start-instance-loop.md
What start_instance_loop does on ProAgentStore
AI agents invoke start_instance_loop to trigger actions in ProAgentStore. 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 start_instance_loop is rated High
Executes autonomous agent operations with external effects; potential for unintended actions despite budget constraints.
From the tool's definition Give agent objective, work autonomously, bounded budget, run id
Attacks that exploit this kind of access
The rule that runs start_instance_loop safely
PolicyLayer is an MCP gateway: it sits between your AI agents and ProAgentStore, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For start_instance_loop, this is the rule to start with:
start_instance_loop 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 ProAgentStore, apply this rule, and every start_instance_loop call is checked against it from then on.
Questions about start_instance_loop
Give an agent an objective and let it work autonomously on the server. Durable: it survives you closing the browser, and its spend is bounded by a budget. Returns a run id — poll it with check_instance_loop. It is categorised as a Execute tool in the ProAgentStore MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the ProAgentStore MCP server in PolicyLayer and add a rule for start_instance_loop: 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 ProAgentStore. Nothing to install.
start_instance_loop 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 start_instance_loop 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 start_instance_loop. 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.
start_instance_loop is provided by the ProAgentStore MCP server (https://mcp.proagentstore.online/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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