Cloud Agents
Orchestrate parallel code review and code-change runs across GitHub repositories with scoped agents, approvals, safety rules, and full run visibility. Available on Pro and above.
Cloud Agents is available on the Pro plan and above. See Account Plans for plan guidance and open the Plans page ↗ to upgrade.
Cloud Agents is the repository workspace in Skytells for running specialized engineering agents against real codebases with clear scope, visible outputs, and operator control. It is designed for teams that want review work, implementation work, and repository checks happening in parallel without losing change discipline.
The product centers on three ideas:
- Parallel work with explicit coordination. Multiple runs can operate across the same repository portfolio while Eve coordinates execution order, handoffs, and state awareness.
- Repository-native control. Runs are attached to repositories, branches, pull requests, and approvals instead of living in an isolated chat silo.
- Operational visibility. Every run has a status, timeline, findings view, artifacts, and approval history so teams can inspect what happened before anything lands.
Visit console.skytells.ai/agents to open the Cloud Agents workspace.
Who Cloud Agents Is For
| Role | Why this surface matters |
|---|---|
| Engineering leads | Reduce queue depth, shorten time to first review, and keep change activity visible without manually coordinating every task. |
| Platform and developer-experience teams | Standardize how automation interacts with repositories, path rules, validation, and approvals. |
| Senior ICs and code owners | Delegate first-pass review and scoped implementation work while preserving final technical judgment. |
| Security, compliance, and release stakeholders | Keep an auditable record of what an agent inspected, prepared, or paused for approval. |
Cloud Agents is most valuable when a team already has real engineering demand but wants tighter control than an ad hoc chat workflow can provide.
How Cloud Agents Works
Cloud Agents does not treat engineering work as a single queue. A repository can receive automated review, scoped execution, and validation workflows concurrently, with safety rules deciding what can proceed automatically and what must stop for a person.
What Teams Usually Improve
| Outcome | How Cloud Agents contributes |
|---|---|
| Faster first-pass review | PR event signals and automated review reduce idle time before a human sees a change. |
| Better backlog throughput | Small and medium implementation tasks can be prepared in parallel instead of waiting for one person to cycle through them serially. |
| Higher change confidence | Validation-after-execute, protected paths, and approvals turn automation into a controlled process instead of a blind write path. |
| Clearer management visibility | Runs, approvals, and usage surfaces show where work is concentrated, blocked, or failing. |
These improvements matter at both the technical and business level: teams ship more predictably, senior engineers spend less time on repetitive first-pass work, and repository owners keep the final decision rights.
When to Use Cloud Agents
PR review at scale
Use Cloud Agents when pull requests are waiting for first-pass review, style feedback, dependency checks, or scoped validation before a human reviewer steps in.
Backlog execution
Use execute runs for small and medium implementation tasks that already have clear acceptance criteria, repository scope, and rollback expectations.
Guardrailed automation
Use repository rules, protected paths, ignore paths, and approval gates when you want automation without granting unrestricted write access to sensitive code.
Operations visibility
Use the runs, approvals, and usage surfaces when engineering managers or platform teams need to understand throughput, failure modes, and quota consumption.
When Not to Use It
- Do not start with auto-execute on a repository that has no path protection, no approval policy, and no clear ownership.
- Do not use broad instructions such as "fix the repo" or "make everything better". Cloud Agents works best when intent, branch, and repository scope are explicit.
- Do not duplicate existing platform setup instructions here. For GitHub authorization, billing, model access, and plan management, use the linked reference docs.
Adoption Pattern That Works
Most teams get better results when they roll Cloud Agents out in stages instead of enabling everything on day one.
- Start with one repository that has clear ownership and a stable pull-request workflow.
- Enable review-first automation before broad execute automation.
- Add protected paths and ignore paths before widening scope.
- Keep execute workflows in Plan or approval-heavy mode until the team trusts the outcomes.
- Expand to more repositories only after run history shows consistent quality.
Workspace Surfaces
Cloud Agents is organized around eight primary tabs in the product workspace:
| Tab | Primary job |
|---|---|
| Overview | High-level status of active and recent runs, including approval backlog and quick actions. |
| Chat | Conversational dispatch surface for scoped tasks, plans, and agent execution. |
| Runs | Full run history with filters for queued, running, awaiting approval, completed, failed, and cancelled work. |
| Usage | Quotas, token consumption, duration, activity charts, and repository concentration. |
| Repositories | Per-repository automation defaults, safety controls, path rules, and signal settings. |
| Approvals | Pending human decisions for merges or other gated actions. |
| Add-ons | Capacity extensions for review runs, execute runs, custom agents, and parallel collaboration tokens. |
| Settings | Global product setup for integrations, custom agents, and approval-related configuration. |
See Workspace Tabs for the page-by-page map.
Product Model
Repositories are the control boundary
Cloud Agents does not run against a vague account-wide code universe. Automation is configured per repository. That is where you decide whether review runs can start automatically, whether execute runs are allowed, which paths are protected, and which noisy paths should be ignored.
Agents are reusable operators
Agents combine a role, a model, instructions, and operating constraints. System agents provide base review and execute behavior. Custom agents let you add repository-specific specialists for tasks such as migration work, documentation maintenance, or dependency hygiene. See Agents.
Runs are the unit of execution
Every review or execute action becomes a run. Runs preserve the input, the progress timeline, the outputs, approval state, and the final disposition. See Runs.
Eve coordinates parallelism
Cloud Agents relies on Eve to coordinate work across agents and repository state. Eve is the orchestration layer that makes concurrent execution useful instead of chaotic.
Business and Technical Fit
| Question | Good fit | Poor fit |
|---|---|---|
| Does the team have recurring review or execution backlog? | Yes, the same work patterns show up repeatedly | No, work is highly irregular and cannot be scoped clearly |
| Is repository ownership clear? | Yes, code owners and approvers are known | No, nobody owns automation policy or final decisions |
| Is the repo operationally mature enough? | CI, branch flow, and release expectations already exist | The repository has no stable workflow yet |
| Does the team want more automation without losing control? | Yes, they want speed and visibility together | No, they want fully unattended change generation across sensitive code |
Related Platform Surfaces
GitHub Integration
Connect repositories with the Console's GitHub OAuth flow. Cloud Agents builds on that integration instead of replacing it.
Model Catalog
Choose the right models for review, execution, and specialized custom agents.
Eve
Understand the orchestration layer coordinating Cloud Agents runs.
Responsible AI
Review the safety and governance posture behind automated actions and approvals.
Documentation
Quickstart
Connect a repository, create or select an agent, and dispatch your first review and execute runs.
Chat & Dispatch
Learn the chat controls, Ask/Plan/Agent modes, and the New Agent Run flow.
Repositories
Configure automation defaults, signals, protected paths, and ignore paths.
Runs
Inspect run statuses, details, findings, artifacts, and approval checkpoints.
Usage & Add-ons
Monitor quotas and expand capacity when your team needs more parallel work.
Settings
Manage integrations, custom agents, and workspace-level configuration surfaces.
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