The GitHub Request Review Tool
Request specific reviewers or teams on a GitHub pull request so an agent can route a change to the right people the moment it’s ready — moving review forward, not waiting.
Reading isn’t doing
Most AI stops at retrieval: it can tell you what happened but can’t do anything about it. The value is in the write — creating the ticket, sending the reply, updating the record — and that demands governance, approval, and an audit trail most integrations lack.
Search-only agents
An agent that can’t act leaves every follow-up to a human.
Risky writes
Ungoverned write access to Slack, Jira, or CRM is dangerous.
Credential sprawl
Tokens scattered across tools are a breach waiting to happen.
No approval path
Consequential actions need a human gate that most bots skip.
GitHub Request Review, without the risk
Capability
What it does
Request reviewers on a pull request.
it requests reviewers or teams on a GitHub pull request.
Assignable to any agent
How it works
Predictable, inspectable behavior
Designed to be reliable.
review requests go through the GitHub API under a governed identity and are logged, so an agent can drive the review process without holding merge authority.
Every call logged
Governance
Private, governed, on-premise
Runs inside your perimeter.
Writes run under role-based policy with optional human approval, using credentials held in your own vault, and every action is logged — so an agent can act across your stack without over-permissioned access or data leaving your control.
Per-tenant, logged
Parameters
The github_request_review tool accepts these inputs when an agent calls it. Required inputs are flagged.
How the GitHub Request Review tool works in practice
GitHub Request Review is an integration & action tool you assign to a VDF AI agent. It requests reviewers or teams on a GitHub pull request. Its hallmarks — GitHub, Review, Route — let an agent rely on it as a dependable step in a larger task rather than a brittle one-off script.
Under the hood, review requests go through the GitHub API under a governed identity and are logged, so an agent can drive the review process without holding merge authority. It expects repo and pr_number as required inputs, so calls are explicit and easy to audit. Every call is scoped to the requesting tenant and written to an audit log, so the capability is safe to run inside a regulated, on-premise environment — the same governance model behind every VDF AI tool.
Teams reach for GitHub Request Review when they need to handle fast routing, ownership, and unblocking. It rarely works alone — pair it with GitHub Create Pull Request, GitHub Merge Pull Request, and Pull Request Review Assistant to build a complete, governed workflow, then compose those steps into an on-premise VDF AI Network.
Where GitHub Request Review pays back
Fast routing
Send a PR to the right reviewers immediately.
Ownership
Request the team that owns the code.
Unblocking
Keep review moving without manual nudging.
Coverage
Ensure every PR gets the right eyes.
Assigned to agents, orchestrated as networks
On VDF AI, an industry’s use cases map to agents, and you assign tools like this one to those agents. Compose multiple agents into a governed, on-premise network.
What changes after you assign it
Questions about the GitHub Request Review tool
What is the GitHub Request Review tool?
It requests reviewers or teams on a GitHub pull request. Assigned to a VDF AI agent, it runs under role-based policy with full audit logging so the capability is safe to use in production.
Can it request a team?
Yes. Provide team_reviewers to request review from a whole team.
Does requesting review approve it?
No. It only routes the PR; approval and merge remain with the reviewers.
What inputs does the GitHub Request Review tool need?
It requires repo and pr_number, and optionally accepts reviewers and team_reviewers. Each parameter is validated when an agent calls the tool, and the full call is logged for audit.
Which tools pair well with GitHub Request Review?
GitHub Request Review is commonly assigned alongside GitHub Create Pull Request, GitHub Merge Pull Request, and Pull Request Review Assistant. On VDF AI you compose several tools and agents into a single governed, on-premise network.
Does it run on-premise?
Yes. Like every VDF AI tool, it can run on-premise or in your sovereign cloud, scoped per user and audit-logged, so your data never leaves your perimeter.
How do agents use it?
You assign the tool to an agent under a role-based policy; the agent calls it as one step in a task, and several agents and tools can be orchestrated together as a governed VDF AI Network.
Assign GitHub Request Review to these agents
These VDF AI agents can be assigned this tool. Open an agent to see the full toolkit it can run.
Tools that work well alongside this one
Where this tool delivers value
Put GitHub Request Review to work
See the GitHub Request Review tool assigned to an agent and orchestrated in a governed, on-premise network.