skyflo

Name: skyflo
Author: skyflo-ai

Verified

Self-Hosted AI Agent for Kubernetes & DevOps. Approval-Gated. Deterministic Control Loop.

115stars

43forks

Python

Installation

# Add to your Claude Code skills
git clone https://github.com/skyflo-ai/skyflo

Getting Started

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Definitions, how marketplaces work, and how to choose between them in 2026.
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Security ReportVerified

Last scanned: 5/30/2026

{
  "issues": [],
  "status": "PASSED",
  "scannedAt": "2026-05-30T16:33:44.534Z",
  "npmAuditRan": true,
  "pipAuditRan": true
}

README.md

Frequently Asked Questions

What is skyflo?

skyflo is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by skyflo-ai. Self-Hosted AI Agent for Kubernetes & DevOps. Approval-Gated. Deterministic Control Loop. It has 115 GitHub stars.

Is skyflo safe to use?

Yes. skyflo passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install skyflo?

Clone the repository with "git clone https://github.com/skyflo-ai/skyflo" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is skyflo written in?

skyflo is primarily written in Python. It is open-source under skyflo-ai on GitHub, so you can review or fork the full source.

Are there alternatives to skyflo?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh skyflo against similar tools.

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Infrastructure automation tools fall into two categories.

CLI assistants translate prompts into shell commands. Autonomous agents execute infrastructure changes without explicit approval.

Neither model guarantees a deterministic execution process or a complete audit trail. And neither one remembers what happened last time.

Skyflo is a self-hosted AI agent for Kubernetes and CI/CD systems. It runs inside your cluster and executes infrastructure operations through a deterministic control loop:

Recall → Plan → Approve → Execute → Verify → Persist

Every mutating tool call is approval-gated, typed, and auditable. Every confirmed incident lesson is saved and recalled on the next relevant task.

Skyflo is not a CLI wrapper, not an autonomous mutation bot, and not a GitOps control plane.

It is an in-cluster AI control layer that enforces safe infrastructure changes before anything reaches production -- and builds operational memory across every session.

Quick Start

Install Skyflo inside your Kubernetes cluster.

Using `Helm`:

helm repo add skyflo https://charts.skyflo.ai
helm repo update skyflo

Create a values.yaml file:

engine:
  secrets:
    llmModel: "gemini/gemini-2.5-pro"
    geminiApiKey: "AI-..."

See helm show values skyflo/skyflo for the full list of configurable values.

helm install skyflo skyflo/skyflo -n skyflo --create-namespace -f values.yaml

Using `curl`:

Get started quickly with the interactive installer.

curl -fsSL https://skyflo.ai/install.sh | bash

Bring your own LLM (OpenAI, Anthropic, Gemini, Groq, self-hosted). See the quick start guide.

Execution Model

Skyflo enforces a strict loop for every infrastructure change:

Recall: retrieve prior incidents, runbooks, and service context from scoped memory
Plan: generate a concrete, replayable plan
Approve: explicit approval for every mutating tool call
Execute: run typed tools via MCP (Kubernetes, Helm, Argo Rollouts, Jenkins)
Verify: validate cluster state against declared intent
Persist: store tool-level audit history and save confirmed lessons to memory

No blind kubectl apply. No silent automation. No untracked changes.

Safety Properties

Approval gate for every mutating tool call, enforced by the engine
Typed tool execution with schema-validated inputs
Persisted audit trail with tool results
Replayable control loop (recall → plan → approve → execute → verify → persist)
Scoped memory with safety scanning (blocks secrets, raw logs, prompt injection)
Runs inside your cluster. No Skyflo telemetry or phone-home
LLM-agnostic via LiteLLM. No vendor lock-in

Supported Tools

Tool	Capabilities
Kubernetes	discovery, get/describe, logs/exec, diff-first apply, rollout history, rollbacks
Helm	template, install/upgrade/rollback, dry-run, diff-first safety
Argo Rollouts	status, pause/resume, promote/cancel, progressive delivery control
Jenkins	jobs/builds/logs, parameters, SCM context, build control

All mutating tool calls require explicit approval.

Demo

Deterministic plans. Explicit approval. Verified execution.

Comparison

Capability	CLI Assistants	Autonomous Agents	GitOps Platforms	Skyflo
Natural language ops	Yes	Yes	Limited	Yes
Mandatory mutation approval	Optional	No	PR-based	Yes
Deterministic control loop	No	No	Partial	Yes
Kubernetes + CI unified	No	Partial	No	Yes
In-cluster deployment	Partial	Partial	Varies	Yes
Team RBAC + audit	No	Limited	Yes	Yes
Real-time execution streaming	No	No	No	Yes

System Architecture

Component	Description
Engine	LangGraph workflow: memory retrieval, planner, approval gate, verifier, persistence, auth/RBAC
MCP Server	Typed tools for Kubernetes, Helm, Argo Rollouts, Jenkins
Command Center	Next.js UI with real-time streaming, approvals, memory context panel, team admin

Details: Architecture

Contributing

Apache 2.0 OSS. High-signal contributions welcome. See CONTRIBUTING.md.

License

Apache 2.0. See LICENSE.