Create a new sprint and assign tickets to it in one operation
AI agents use plan_sprint to create or update resources in Code Context — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Code Context environment.
An AI agent can call plan_sprint faster than any human can review — one bad instruction and it creates or modifies resources in Code Context by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
Create a new sprint and assign tickets to it in one operation. It is categorised as a Write tool in the Code Context MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Code Context MCP server in PolicyLayer and add a rule for plan_sprint: 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 Code Context. Nothing to install.
plan_sprint 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 plan_sprint 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 plan_sprint. 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.
plan_sprint is provided by the Code Context MCP server (velimirmueller/vlm-code-context-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.