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.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add omnigent-ai/omnigent --skill cross-reviewgit 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/cross-review)<a href="https://agentmods.dev/skills/omnigent-ai/omnigent/cross-review"><img src="https://agentmods.dev/badge/skills/omnigent-ai/omnigent/cross-review/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/cross-review"><img src="https://agentmods.dev/badge/skills/omnigent-ai/omnigent/cross-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00037 | $0.01059 |
| Opus 5 | $0.00018 | $0.00530 |
| Sonnet 5 | $0.00007 | $0.00212 |
| Haiku 4.5 | $0.00004 | $0.00106 |
Grade A, and why
cross-review 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 9d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
cross-review — independent verification
The implementer never signs off on its own work — a different model does, and review is a sub-agent that returns a structured report, not a transcript anyone needs to read through.
Procedure
- Get the task's diff —
sys_os_shell("gh pr diff <pr>")(orgit -C .worktrees/<task_id> diff main...HEAD). - Run the deterministic gates first — tests / lint / typecheck via
sys_os_shell. If red, re-dispatch the implementer to drive it green first; don't involve the reviewer yet. If a pytest result's count must be recorded or reconciled, collect ground truth withpython -m pytest --collect-only -q <same files>against the exact file set/command/commit the implementer reported. Never usegrep -c 'def test_'as a pytest count: it counts functions, not collected cases, and misses parametrized case expansion. - Dispatch a DIFFERENT-vendor sub-agent as reviewer: pick any AVAILABLE worker
whose vendor differs from the implementer's —
claude_code,codex,opencode,cursor,hermes,agy, orpi(e.g. Claude built it → any ofcodex/opencode/cursor/hermes/agy/pi, and so on). Use a task-based title such asreview-auth-refactor, never the raw vendor name:sys_session_send(agent="claude_code"|"codex"|"opencode"|"cursor"|"hermes"|"agy"|"pi", title="review-<task_slug>", args={purpose: "review", input: "<the diff> + <the acceptance contract>. Review ONLY against the contract. Report blocking / non-blocking / suggestions. Do not edit code."}). Give it the diff as text — do NOT point it at the implementer's worktree. Fetch the diff and emit thesys_session_sendcall in the SAME turn you decide to review — never end a turn having only announced "I'll load cross-review and fetch the diff" with no tool call (that dropped turn stalls the run; nothing dispatches and no inbox wake arrives). Once the reviewer dispatch is in flight, end your turn; collect the inbox-delivered structured report withsys_read_inboxwhen it returns. Usesys_session_get_historyonly to debug an empty or unclear review result. - The reviewer SURFACES issues; it does not fix them.
- For each blocking issue: add a fix-task to the registry scoped to the
same worktree, and send the concrete fixes back to the SAME implementer
conversation via
sys_session_send— reuse the original implementer'sagent+title(or address it bysession_id) withpurpose: "implement", so the worker keeps its worktree/branch context and updates its existing PR. A new title would spawn a fresh worker with no memory of the task. Then loop to step 1. - When gates are green AND there are zero blocking issues, the PR passes review — mark it ready in the registry (with its PR URL) and leave it for the human to merge. polly does NOT merge it.
- If the contract can't be satisfied after a few loops, stop and escalate to the user with specifics.
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.
- 9d ago First seen · 69 lines · 37 tokens per session scan A 2c5c0981cc35
cross-review is a skill published in the GitHub repository omnigent-ai/omnigent (9,768 stars, last pushed today), licensed Apache-2.0. It adds 37 tokens to every session and 1,059 once invoked, about $0.0002 per session on Opus 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.
Other skills, from other repositories
code-review
Code review assistance with linting, style checking, and best practices.
cocoreview
CocoReview — structured code review with six-severity findings vocabulary, progressive disclosure architecture, and universal anti-pattern baseline. Invoked via $review [file] [--complexity] [--security] [--architecture] [--language ].
review-loop
Run the adversarial verification loop — implement, then hand the change to a fresh checker that did not write it, fix what it finds, and re-dispatch until APPROVE. Use before claiming any behavioural change is done, and on requests like "review loop", "adversarial review", "independent review", "get this verified"…
lean-review
CocoLean diff-scoped over-engineering audit — scans uncommitted git diff and applies five classification tags (delete/stdlib/native/yagni/shrink) to identify unnecessary surface area before commit.
review-export
Export CocoReview reports as markdown, html, or pdf-ready status artifacts. Usage: $review export markdown|html|pdf [report-path].
factory-rereview
Re-review a pull request after a push — reconcile the previous review against the new commits, look for new defects the push introduced, then a fresh pass over the whole PR, and finish with a verdict on the PR.