assign_copilot_to_issue

SERVERGitHub SOURCEoci:ghcr.io/github/github-mcp-server:1.3.0

High RISK CLASS

Category Execute

Parameters 50 required

Recommended Rate-limitedsee the rule below

Registry record Grade D, identity verified Pull the record →

This record as markdown: /tools/github/assign-copilot-to-issue.md

WHAT IT DOES

What assign_copilot_to_issue does on GitHub

AI agents invoke assign_copilot_to_issue to trigger actions in GitHub. 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.

Parameter	Type	Required	Description
`repo`	string	—	Repository name
`owner`	string	—	Repository owner
`base_ref`	string	—	Git reference (e.g., branch) that the agent will start its work from. If not specified, defaults to the repository's default branch
`issue_number`	number	—	Issue number
`custom_instructions`	string	—	Optional custom instructions to guide the agent beyond the issue body. Use this to provide additional context, constraints, or guidance that is not captured in

Parameters from the server's own tool schema.

RISK

Why assign_copilot_to_issue is rated High

This tool triggers an external AI agent (GitHub Copilot) to autonomously work on a GitHub issue and potentially create pull requests with code changes. It initiates an automated workflow with real side effects (code generation, PR creation), making it Execute category. The blast radius is high because an AI agent could produce unwanted code changes or PRs at scale.

From the tool's definition Assign Copilot to a specific issue... a Pull Request created with source code changes to resolve the issue

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs assign_copilot_to_issue safely

PolicyLayer is an MCP gateway: it sits between your AI agents and GitHub, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For assign_copilot_to_issue, this is the rule to start with:

assign_copilot_to_issue Rate-limited

assign_copilot_to_issue 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "assign_copilot_to_issue": {
      "limits": [
        {
          "counter": "assign_copilot_to_issue_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect GitHub, apply this rule, and every assign_copilot_to_issue call is checked against it from then on.

FAQ

Questions about assign_copilot_to_issue

What does the assign_copilot_to_issue tool do? +

Assign Copilot to a specific issue in a GitHub repository. This tool can help with the following outcomes: - a Pull Request created with source code changes to resolve the issue More information can be found at: - https://docs.github.com/en/copilot/using-github-copilot/using-copilot-coding-agent-to-work-on-tasks/about-assigning-tasks-to-copilot. It is categorised as a Execute tool in the GitHub MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

What parameters does assign_copilot_to_issue accept? +

assign_copilot_to_issue accepts 5 parameters: repo, owner, base_ref, issue_number, custom_instructions. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on assign_copilot_to_issue? +

Register the GitHub MCP server in PolicyLayer and add a rule for assign_copilot_to_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 GitHub. Nothing to install.

What risk level is assign_copilot_to_issue? +

assign_copilot_to_issue is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit assign_copilot_to_issue? +

Yes. Add a rate_limit block to the assign_copilot_to_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.

How do I block assign_copilot_to_issue completely? +

Set action: deny in the PolicyLayer policy for assign_copilot_to_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.

What MCP server provides assign_copilot_to_issue? +

assign_copilot_to_issue is provided by the GitHub MCP server (oci:ghcr.io/github/github-mcp-server:1.3.0). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

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Guides

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