execute_agent_builder_plan
Execute a reviewed agent-builder plan to create or scaffold a new agent template. This can create durable platform state and, for a scaffold plan, repository material; preview first and pass the exact confirmation only when the plan is the one you intend to create.
This record as markdown: /tools/io-github-proagentstore-platform/execute-agent-builder-plan.md
What execute_agent_builder_plan does on ProAgentStore
AI agents invoke execute_agent_builder_plan 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 execute_agent_builder_plan is rated High
Creates platform state and repository material via plan execution; requires confirmation but effects depend on plan arguments.
From the tool's definition Execute a reviewed agent-builder plan to create or scaffold a new agent template. This can create durable platform state
Attacks that exploit this kind of access
The rule that runs execute_agent_builder_plan 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 execute_agent_builder_plan, this is the rule to start with:
execute_agent_builder_plan 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 execute_agent_builder_plan call is checked against it from then on.
Questions about execute_agent_builder_plan
Execute a reviewed agent-builder plan to create or scaffold a new agent template. This can create durable platform state and, for a scaffold plan, repository material; preview first and pass the exact confirmation only when the plan is the one you intend to create. 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 execute_agent_builder_plan: 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.
execute_agent_builder_plan 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 execute_agent_builder_plan 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 execute_agent_builder_plan. 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.
execute_agent_builder_plan 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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