Comparison from first-party sources, read Oct 9, 2026

Skyflo vs Omnigent

Omnigent is an open-source meta-harness: a common layer over Claude Code, Codex, Pi, and agents you write yourself. Skyflo is a Mac app and control plane for the agents you already use, organized into missions with one access mode each.

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A source-dated comparison of two orchestration layers, including where Omnigent is the better fit.

At a glance8 dimensions, no winner score

OmnigentDocumented strength

Omnigent provides a broad open-source meta-harness: declarative agents, direct and native harness modes, BYOK and compatible gateways, stateful policies, OS sandboxing, shared live sessions, multi-repository sessions, scheduled automations, mobile clients, and a Databricks-managed beta.

SkyfloWhere it sits

Skyflo is a proprietary Mac app rather than a framework: it runs its own agent and seven external agents under one access mode per mission, keeps an append-only record on your Mac, and leaves source-linked memory you review.

12 first-party sourcesRead Oct 9, 2026

The decision.

Do you want an open-source meta-harness to compose and self-host agent services, or a finished Mac app that runs the agents you already use?

Omnigent, which Databricks started and open-sourced, gives you declarative agents, stacked policies, OS sandboxing, live co-driving and a managed Databricks beta. Skyflo is a proprietary Mac app: missions run your existing agents under one access mode, with a record and source-linked memory on your Mac.

Not run by Skyflo. Skyflo does not run Omnigent. Both can run Claude Code, Codex and Pi; Omnigent is a framework you deploy, Skyflo an app you install.

Choose Omnigent when

You want an Apache-2.0 agent runtime that you can self-host or deploy behind a shared server.
Broad current harness support, declarative YAML agents, and real-time co-driving are central requirements.
You want Omnigent's policy stack, OS sandbox, mobile clients, or Databricks integration.

Choose Skyflo when

You want a finished Mac app that runs Codex, Claude Code, Cursor Agent and four more without writing agent definitions.
Memory should be learned from finished missions, linked to its source, and kept automatically only when the evidence supports it.
Skills should come from workflows verified in two repositories or from a task you teach once, and any change Skyflo makes to what it learned or how it routes should be revertible.

You might use both when

Use Omnigent for agent services you compose, share, or self-host, and Skyflo for missions on your Mac that run the agents you already use.

Skyflo vs Omnigent, dimension by dimension.

The same 8 dimensions run on every engineering comparison, including the ones where Omnigent is stronger. A row reading “not addressed” means the reviewed documentation does not cover it, which is not the same as the product lacking it.

Omnigent and Skyflo across 8 dimensions
Dimension	Omnigent	Skyflo
Primary unit of work	A declarative agent and persistent session, with built-in multi-agent examples such as Polly and Debby.	A mission: one goal with its conversation, the agents working on it, their approvals, and its record. It persists across sessions and goes idle rather than closing.
Execution environment	Local or self-hosted runners, remote sandbox providers, Kubernetes and hosted deployments, plus a Databricks-managed beta.	Agents run on your Mac by default. On a paid plan you can start or move a mission to Skyflo Cloud, a machine Skyflo runs for that mission, which keeps working while your Mac sleeps. Only Codex and Skyflo's own agent run there; Claude Code stays on your Mac. A mission started there from a GitHub repository opens a pull request.
Agent and model choice	Claude Code, Codex, and the OpenAI Agents SDK are fully supported; Copilot, Cursor, OpenCode, and Pi are maintained; others, including Grok Build, are community-supported or run over ACP. Models come from provider keys, subscriptions, gateways, local endpoints, and Databricks.	Skyflo's own agent plus seven external agents: Codex, Claude Code, Cursor Agent, Antigravity, Grok CLI, OpenCode, and Pi, and one custom ACP agent added through a manifest file. External agents use their own sign-in and models; Skyflo's own agent uses the managed models every paid plan includes, or your Moonshot or Z.ai key. Orchestrate runs several on one mission and can pick the lead.
Cross-repository coordination	Polly coordinates separate harnesses in worktrees, and a session can track pull requests and start sandboxes across several GitHub repositories.	A workspace is an ordered set of up to eight registered Git checkouts, and one mission can span them. In Skyflo Cloud a mission spans one to five. Each writing specialist works in its own worktree, so edits stay apart while the work runs; integrating them is still a change you review.
Approval and mutation boundaries	Stateful ALLOW, ASK, and DENY policies stack at session, agent configuration, and server levels; OS sandboxing covers supported local tool execution with documented scope limits.	One access mode governs every agent on a mission, Skyflo's own and the external ones. Skyflo answers each agent's permission requests by that mode and records the decision. In Full access, the default for a new Auto mission, prompts are off and folder confinement is lifted. Orchestrate starts at Ask for approval, and Plan mode waits for you to approve the plan.
Independent review	Polly sends each diff to a reviewer from a different vendor and never merges, and a read-only policy can make an agent report-only; the reviewed sources do not make a read-only final reviewer the default for every session.	In Orchestrate missions, Skyflo adds a separate reviewer by strategy and risk, and Skyflo's own agent can start one. The reviewer can read, search, ask, and report, but cannot edit files. Not every mission is reviewed, and a review is a second opinion, not a guarantee.
Browser, terminal, and automation evidence	Terminal, web, desktop, mobile, Slack, REST, Python, and an embedded browser are documented around persisted server sessions.	Code, browser, terminal, and automations share one workspace, where you and Skyflo's own agent work in the same browser and terminal. On paid plans, missions sign in to websites with your saved sign-ins, passwords kept in the Keychain, and agents can work in any Mac app through Skyflo Computer Use, stopping before a submit, send or payment outside Full access. Each mission keeps an append-only record on your Mac of approvals, Skyflo tool calls, including external agents' calls through Skyflo's tools, and review findings, every event hash-linked to the one before it.
Cross-mission memory, provenance, and user control	Sessions and artifacts persist in Postgres, CockroachDB, or SQLite, and optional Hindsight tools let an agent retain, recall, and reflect on memory across runs with a Hindsight API key.	Personal memory stored on your Mac, learned from finished missions with a link to its source. Skyflo keeps a memory when the evidence supports it; otherwise it waits for you to keep, correct, or dismiss it, and you can remove any memory later. A workflow verified in two repositories can become a Skill once you or an independent agent approves it, and you can also teach a Skill a task once, by showing it, saving a finished mission or attaching the steps. Reverting a Skill or a routing change alters what Skyflo does next, not past work.

First-party sources, dated.

Last reviewed Oct 9, 2026

Every statement about Omnigent on this page is limited to behavior documented on these pages, on the date they were read. Where they do not cover a dimension, the table says so instead of guessing.

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