kelos-dev / kelos

Kelos Orchestrate autonomous AI coding agents on Kubernetes. Quick Start · Kelos Developing Kelos · Examples · Reference · YAML Manifests Kelos lets you **define your development workflow as Kubernetes resources** and run it continuously. Declare what triggers agents, what they do, and how they hand off — Kelos handles the rest. Kelos develops Kelos through seven TaskSpawners run 24/7: triaging issues, planning implementations, fixing bugs, responding to PR feedback, testing DX, brainstorming improvements, and tuning their own prompts. See the full pipeline below. Supports **Claude Code**, **OpenAI Codex**, **Google Gemini**, **OpenCode**, **Cursor**, and custom agent images. How It Works Kelos orchestrates the flow from external events to autonomous execution: You define what needs to be done, and Kelos handles the "how" — from cloning the right repo and injecting credentials to running the agent and capturing its outputs (branch names, commit SHAs, PR URLs, and token usage). Core Primitives Kelos is built on four resources: • **Tasks** — Ephemeral units of work that wrap an AI agent run. • **Workspaces** — Persistent or ephemeral environments (git repos) where agents operate. • **AgentConfigs** — Reusable bundles of agent instructions ( , ), plugins (skills and agents), and MCP servers. • **TaskSpawners** — Orchestration engines that react to external triggers (GitHub, Cron) to automatically manage agent lifecycles. TaskSpawner — Automatic Task Creation from External Sources TaskSpawner watches external sources (e.g., GitHub Issues) and automatically creates Tasks for each discovered item. Kelos Developing Kelos Kelos develops itself. Seven TaskSpawners run 24/7, each handling a different part of the development lifecycle — fully autonomous. | TaskSpawner | Trigger | Model | Description | |---|---|---|---| | **kelos-workers** | GitHub Issues ( ) | Opus | Picks up issues, creates or updates PRs, self-reviews, and ensures CI passes | | **kelos-pr-responder** | GitHub Pull Requests ( , ) | Opus | Re-engages on PR review feedback and updates the existing branch incrementally | | **kelos-planner** | GitHub Issues ( comment) | Opus | Investigates an issue and posts a structured implementation plan — advisory only, no code changes | | **kelos-triage** | GitHub Issues ( ) | Opus | Classifies issues by kind/priority, detects duplicates, and recommends an actor | | **kelos-fake-user** | Cron (daily 09:00 UTC) | Sonnet | Tests DX as a new user — follows docs, tries CLI workflows, files issues for problems found | | **kelos-fake-strategist** | Cron (every 12 hours) | Opus | Explores new use cases, workflow improvements, and integration opportunities | | **kelos-self-update** | Cron (daily 06:00 UTC) | Opus | Reviews and tunes prompts, configs, and workflow files — the pipeline improves itself | Here's a trimmed snippet of — enough to show the pattern: The key pattern is — this creates a feedback loop where the agent works autonomously until it needs human input, then pauses. Removing the label re-queues the issue on the next poll. See the full manifest at and the README for setup instructions. Why Kelos? AI coding agents are evolving from interactive CLI tools into autonomous background workers — managed like infrastructure, not invoked like commands. Kelos provides the framework to manage this transition at scale. • **Workflow as YAML** — Define your development workflow declaratively: what triggers agents, what they do, and how they hand off. Version-control it, review it in PRs, and GitOps it like any other infrastructure. • **Orchestration, not just execution** — Don't just run an agent; manage its entire lifecycle. Chain tasks with and pass results (branch names, PR URLs, token usage) between pipeline stages. Use to build event-driven workers that react to GitHub issues, PRs, or schedules. • **Host-isolated autonomy** — Each task runs in an isolated, ephemeral Pod with a freshly cloned git workspace. Agents have no access to your host machine — use scoped tokens and branch protection to control repository access. • **Standardized interface** — Plug in any agent (Claude, Codex, Gemini, OpenCode, Cursor, or your own) using a simple container interface. Kelos handles credential injection, workspace management, and Kubernetes plumbing. • **Scalable parallelism** — Fan out agents across multiple repositories. Kubernetes handles scheduling, resource management, and queueing — scale is limited by your cluster capacity and API provider quotas. • **Observable & CI-native** — Every agent run is a first-class Kubernetes resource with deterministic outputs (branch names, PR URLs, commit SHAs, token usage) captured into status. Monitor via , manage via the CLI or declarative YAML (GitOps-ready), and integrate with ArgoCD or GitHub Actions. Quick Start Get running in 5 minutes (most of the time is gathering credentials). Prerequisites • Kubernetes cluster (1.28+) Don't have a cluster? Create one locally with kind • Install kind (requires Docker) • Create a cluster: This creates a single-node cluster and configures your kubeconfig automatically. • Install the CLI Alternative: install from source • Install Kelos This installs the Kelos controller and CRDs into the namespace. Verify the installation: • Initialize Your Config Edit : How to get your credentials **Claude OAuth token** (recommended for Claude Code): Run locally, then copy the token from . **Anthropic API key** (alternative for Claude Code): Create one at console.anthropic.com. Set instead of in your config. **Codex OAuth credentials** (for OpenAI Codex): Run locally, then reference the auth file in your config: Or set with an OpenAI API key instead. **GitHub token** (for pushing branches and creating PRs): Create a Personal Access Token with scope (and if your repo uses GitHub Actions). **GitHub App** (recommended for production/org use): For organizations, GitHub Apps are…