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 feature-designgit 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/feature-design)<a href="https://agentmods.dev/skills/omnigent-ai/omnigent/feature-design"><img src="https://agentmods.dev/badge/skills/omnigent-ai/omnigent/feature-design/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/feature-design"><img src="https://agentmods.dev/badge/skills/omnigent-ai/omnigent/feature-design.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 | $0.00024 | $0.00410 |
| Opus 5.5 | $0.00010 | $0.00164 |
| Sonnet 5.5 | $0.00005 | $0.00082 |
| Haiku 4.5 | $0.00002 | $0.00041 |
Grade A, and why
feature-design 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 today.
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.
What it actually says
Design
Read the code each requirement touches before choosing. Then record, for the PR
and the handoff's design and cujs fields:
- Chosen design: where it plugs in (layers, APIs, configuration, flags) and
how each requirement is met. Follow the repository's existing patterns and
CLAUDE.md. - Alternatives considered: each realistic alternative and why you rejected it. One or two well-argued alternatives beat a long list.
- Risks: compatibility, migration, performance, and security concerns, and how the design handles them.
- CUJ coverage: mark each CUJ covered or not covered. Every not-covered CUJ gets a reason (out of scope, needs a separate feature, blocked by a missing capability). Cover at least one CUJ.
Decide, or stop for a human
Make product and technical choices yourself when the ticket, code, docs, or existing conventions support one. Write the choice and the alternatives down; reviewers judge them on the PR.
Stop with needs_more_info before implementation only when a choice really
needs a human decision, for example:
- a product-design question the ticket leaves open and the product gives no basis to settle;
- a technical choice that is hard to reverse, such as a public API, data model, or stored-format change, where the options trade off differently and nothing in the ticket or code favors one;
- a ticket that contradicts existing behavior other users depend on.
In that case ticket_comment lays out the options, their tradeoffs, and your
recommendation, so a human can answer on the ticket and rerun the agent. Small
or easily reversed choices never justify stopping.
Then load feature-implement.
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.
- today First seen · 43 lines · 24 tokens per session scan A 7d97f546c509
feature-design is a skill published in the GitHub repository omnigent-ai/omnigent (10,855 stars, last pushed today), licensed Apache-2.0. It adds 24 tokens to every session and 410 once invoked, about $0.0001 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 2026-10-17.
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