Explain a code quality issue detected by OCR. Returns detailed explanation, category context, and fix guidance for the AI agent to act on.
AI agents call explain_issue to retrieve information from Open Code Review without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and returns informational content about a previously detected issue — explanations, context, and guidance. It has no side effects; it only reads/queries existing issue data and formats it for consumption. No data is created, modified, executed, or deleted.
From the tool's definition 'Explain a code quality issue detected by OCR. Returns detailed explanation, category context, and fix guidance'
Documented attack patterns abuse exactly the kind of access explain_issue gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Open Code Review, and nothing reaches the server without passing your rules. This is the rule we recommend for explain_issue:
{
"version": "1",
"default": "deny",
"tools": {
"explain_issue": {}
}
}explain_issue is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Explain a code quality issue detected by OCR. Returns detailed explanation, category context, and fix guidance for the AI agent to act on. It is categorised as a Read tool in the Open Code Review MCP Server, which means it retrieves data without modifying state.
Register the Open Code Review MCP server in PolicyLayer and add a rule for explain_issue: 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 Open Code Review. Nothing to install.
explain_issue is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the explain_issue 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 explain_issue. 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.
explain_issue is provided by the Open Code Review MCP server (raye-deng/open-code-review). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Open Code Review, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
4 Open Code Review tools catalogued and risk-classified — across an index of 43,000+ MCP servers.