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/cli-setup-verify/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/cli-setup-verify)<a href="https://agentmods.dev/skills/omnigent-ai/omnigent/cli-setup-verify"><img src="https://agentmods.dev/badge/skills/omnigent-ai/omnigent/cli-setup-verify/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/cli-setup-verify"><img src="https://agentmods.dev/badge/skills/omnigent-ai/omnigent/cli-setup-verify.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 | $0.00176 | $0.03175 |
| Opus 5.5 | $0.00070 | $0.01270 |
| Sonnet 5.5 | $0.00035 | $0.00635 |
| Haiku 4.5 | $0.00018 | $0.00317 |
Grade A, and why
cli-setup-verify scanned grade A with 0 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 2mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verifying the Omnigent CLI setup & UX in a closed loop
The Omnigent CLI's first impression is: curl | sh → run omnigent → pick a
model credential → start a session. This skill lets an agent enter that flow,
examine the UI/UX, and prove whether a change is verifiable — without a
browser, without real credentials, and without ever touching the developer's
real ~/.omnigent.
The engine is verify_cli.py (next to this file). It drives the real
omnigent binary through a pseudo-terminal (pexpect) inside a throwaway
sandbox, captures what renders, runs assertions, and prints one machine-readable
SUMMARY {json} line.
The whole point is a verifiable loop, not a one-shot check:
- Run a scenario on the unfixed code → baseline (
--label before).- Make the change.
- Run the same scenario →
--label after.- Diff the two
SUMMARYlines. A fix is "verifiable" only if a concrete check or note flips between the two runs. If it doesn't flip, you can't prove the fix did anything — go back to step 2.
Why this is safe (read first)
The real ~/.omnigent here can be many GB (chat DB, runner logs, native
harness state). The sandbox isolates every write three ways:
HOMEis redirected into the sandbox by default. This is the load-bearing one.OMNIGENT_CONFIG_HOME/OMNIGENT_DATA_DIR(omnigent/cli.py_CONFIG_HOME_ENV_VAR/_DATA_DIR_ENV_VAR) redirect config + data — but the CLI's diagnostics logger ignores them: it writes a per-invocationcli-*.logunderstate_dir(), hardcoded toPath.home()/.omnigent/logs(omnigent_ui_sdk/terminal/_config.py). So only redirectingHOMEkeeps a non-help command (config list, the setup PTY spawns,server stop) from writing into the real home. The driver does this for you.--strip-pathreducesPATHsonode/tmux/claude/codexread as "not installed" → the true fresh-machine cold start.- Ambient model keys (
ANTHROPIC_API_KEY, …) are stripped from the child env unless you pass--keep-env-creds.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 211 lines · 176 tokens per session scan E 48ded57cb1fb
cli-setup-verify is a skill published in the GitHub repository omnigent-ai/omnigent (11,100 stars, last pushed today), licensed Apache-2.0. It adds 176 tokens to every session and 3,175 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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