task_planning
AI agents use task_planning to create or update resources in AI Pull Request Generator — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your AI Pull Request Generator environment.
An AI agent can call task_planning faster than any human can review — one bad instruction and it creates or modifies resources in AI Pull Request Generator by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
task_planning. It is categorised as a Write tool in the AI Pull Request Generator MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the AI Pull Request Generator MCP server in PolicyLayer and add a rule for task_planning: 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 AI Pull Request Generator. Nothing to install.
task_planning is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the task_planning 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 task_planning. 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.
task_planning is provided by the AI Pull Request Generator MCP server (shougakusei/plan_pr_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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