handle_run_review · Code Context MCP: Risk & Policy

WHAT IT DOES

What handle_run_review does on Code Context

AI agents use handle_run_review 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.

WHY IT NEEDS A POLICY

Why handle_run_review needs a policy

An AI agent can call handle_run_review 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

Recommended rule Ready

Verdict

handle_run_review Rate-limited

handle_run_review stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "handle_run_review": {
      "limits": [
        {
          "counter": "handle_run_review_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Code Context, so you can run agents against it safely.

FAQ

Questions about handle_run_review

What does the handle_run_review tool do? +

Handle the sprint review ceremony triggered from the dashboard. Shows sprint completion summary and demo. 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.

How do I enforce a policy on handle_run_review? +

Register the Code Context MCP server in PolicyLayer and add a rule for handle_run_review: 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.

What risk level is handle_run_review? +

handle_run_review is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit handle_run_review? +

Yes. Add a rate_limit block to the handle_run_review 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.

How do I block handle_run_review completely? +

Set action: deny in the PolicyLayer policy for handle_run_review. 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.

What MCP server provides handle_run_review? +

handle_run_review 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.