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 duyet/oma --skill create-agentgit clone --depth 1 https://github.com/duyet/omaWrote 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/duyet/oma/create-agent)<a href="https://agentmods.dev/skills/duyet/oma/create-agent"><img src="https://agentmods.dev/badge/skills/duyet/oma/create-agent/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/duyet/oma/create-agent"><img src="https://agentmods.dev/badge/skills/duyet/oma/create-agent.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 | $0.00088 | $0.00800 |
| Opus 5.5 | $0.00035 | $0.00320 |
| Sonnet 5.5 | $0.00018 | $0.00160 |
| Haiku 4.5 | $0.00009 | $0.00080 |
Grade A, and why
create-agent 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 1mo 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.
This is a copy
92% identical to create-agent — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
oma Agent Creator
What is oma?
oma is an open-source platform for building, deploying, and managing AI agents. Think of it as a managed runtime — you define an agent (model + system prompt + tools), the platform handles sandboxed execution, credential management, and session state.
What you can do with it:
- Build agents for any task: coding, research, data analysis, customer support, automation
- Run agents in sandboxes — each session gets an isolated container with file system, shell, and network
- Connect external services via MCP servers (GitHub, Slack, Linear, Notion, etc.) with OAuth
- Use any LLM — Anthropic, OpenAI, DeepSeek, or any OpenAI-compatible provider
- Install community skills from ClawHub to extend agent capabilities
- Manage credentials securely in vaults — agents get scoped access, secrets never leak
- Collaborate — multi-user workspace with API key access for CLI/SDK integration
Creating an Agent
Flow
-
Understand the goal — ask what the agent should do. If vague, one question: "What's the main task?" Two rounds max, then build.
-
Pick the model — check
/v1/model_cardsfirst. Defaults:- Complex/coding:
claude-opus-4-6 - General (default):
claude-sonnet-4-6 - Simple/fast:
claude-haiku-4-5-20251001 - OpenAI:
gpt-4o,o3
- Complex/coding:
-
Write system prompt — specific, actionable, bounded. Not generic.
-
Select tools — default
agent_toolset_20260401(file ops, bash, web) covers most cases. -
Create:
POST /v1/agents { "name", "model", "system", "tools": [{"type":"agent_toolset_20260401"}] } -
Next steps — offer to create session, configure skills, set up model card.
Platform Quick Ref
Agents need a session to run. Sessions need an environment (sandbox).
| Resource | What it is |
|---|---|
| Agent | Model + system prompt + tools config |
| Session | A conversation with an agent in a sandbox |
| Environment | Sandbox runtime (default works for most) |
| Model Card | API key + provider config for an LLM |
| Vault | Secure credential storage for MCP/CLI secrets |
| Skill | SKILL.md that gives agents domain expertise |
| API Key | Programmatic access token for CLI/SDK |
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.
- 1mo ago First seen · 78 lines · 88 tokens per session scan A 5b3970c5b84b
create-agent is a skill published in the GitHub repository duyet/oma (10 stars, last pushed 9d ago), licensed Apache-2.0. It adds 88 tokens to every session and 800 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to create-agent, differing in 10 lines, and is treated as a copy.
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