Omnigent is an open-source orchestration layer for running and coordinating different AI coding agents through one system. It is for developers who want to combine agents, apply policies and sandboxing, and continue sessions across devices. The catalogue add-ons extend its agent workflows.
Borrowing it
Nothing to install: this file belongs to omnigent-ai/omnigent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/omnigent-ai/omnigent/main/.claude/skills/antigravity-native-e2e-dev/SKILL.mdgit clone --depth 1 https://github.com/omnigent-ai/omnigentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/omnigent-ai/omnigent/antigravity-native-e2e-dev)<a href="https://agentmods.dev/skills/omnigent-ai/omnigent/antigravity-native-e2e-dev"><img src="https://agentmods.dev/badge/skills/omnigent-ai/omnigent/antigravity-native-e2e-dev/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/omnigent-ai/omnigent/antigravity-native-e2e-dev"><img src="https://agentmods.dev/badge/skills/omnigent-ai/omnigent/antigravity-native-e2e-dev.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00170 | $0.04467 |
| Opus 5.5 | $0.00068 | $0.01787 |
| Sonnet 5.5 | $0.00034 | $0.00893 |
| Haiku 4.5 | $0.00017 | $0.00447 |
Grade E, and why
antigravity-native-e2e-dev scanned grade E with 3 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
# curl -fsSL https://antigravity.google/cli/install.sh | bash # then restart shell Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
# rm -rf "$(.venv/bin/python -c "from omnigent.antigravity_native_bridge import bridge_dir_for_bridge_id as d; print(d('$CONV'))")" Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
# curl -fsSL https://antigravity.google/cli/install.sh | bash # then restart shell How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Antigravity native harness: end-to-end dev & testing (local server/runner)
The antigravity-native harness wraps the real Antigravity agy TUI (the
agy CLI, installed from antigravity.google/cli/install.sh). omnigent antigravity ensures a host daemon, the daemon-spawned runner launches agy
in a runner-owned tmux terminal, and your TTY attaches to it. This is not
the in-process antigravity Gemini-SDK harness — that one runs google-antigravity
with separate SDK settings; this one drives the agy CLI and mirrors it
over connect-RPC. This skill is the proven recipe for running it for real
against a live local server + runner — not just the unit tests.
Like the other native harnesses, the runner imports from your current checkout, so testing here exercises exactly the code you're on. (CWD/venv selects the code, not
PYTHONPATH.)
What actually runs where
your TTY ── (attach / pexpect) ──► omnigent antigravity (CLI, local)
│ ensures
▼
host daemon ──► local Omnigent server (AP)
│ spawns ▲
▼ connect-RPC │ HTTP
runner ── launches ──► agy (TUI, in tmux)
│ │
├── write path: type web turns into the TUI
│ (tmux bracketed paste → real USER_INPUT step)
└── read path: RPC read driver mirrors agy's
trajectory steps back into the session
Three transports, easy to confuse:
- Write path = typing into the TUI. Every web/mobile turn is typed into the
agy pane via tmux (
inject_user_message_via_tui), creating a realCORTEX_STEP_TYPE_USER_INPUTstep on the same cascade the TUI shows (#1156/#1158). It is not delivered overSendUserCascadeMessage(that headless RPC path was retired; theantigravity_native.pymodule header still says "delivered via the RPC" — that's stale doc-lag, the executor is authoritative). - Read path = RPC.
antigravity_native_readerpolls/streams agy's connect-RPC trajectory steps and mirrors them into the Omnigent session. - Control = RPC. Interrupt is
CancelCascadeSteps; a tool/permission prompt is answered viaHandleCascadeUserInteraction(surfaced as an Omnigent elicitation).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago Changed · +6 lines c31a8567870f
- 26d ago Changed 808646a98793
- 2mo ago First seen · 296 lines · 170 tokens per session scan E 6e9df6d23235
antigravity-native-e2e-dev is a skill published in the GitHub repository omnigent-ai/omnigent (11,100 stars, last pushed today), licensed Apache-2.0. It adds 170 tokens to every session and 4,467 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it E with 3 findings (downloads and executes remote code, recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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