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 agentmods add skills/openma-ai/open-managed-agents/create-agentnpx skills add openma-ai/open-managed-agents --skill create-agentgit clone --depth 1 https://github.com/openma-ai/open-managed-agentsWrote 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/openma-ai/open-managed-agents/create-agent)<a href="https://agentmods.dev/skills/openma-ai/open-managed-agents/create-agent"><img src="https://agentmods.dev/badge/skills/openma-ai/open-managed-agents/create-agent.svg" alt="Measured on agentmods" 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 | $0.00090 | $0.00805 |
| Opus 5 | $0.00045 | $0.00402 |
| Sonnet 5 | $0.00018 | $0.00161 |
| Haiku 4.5 | $0.00009 | $0.00081 |
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 5d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- create-agent — 92% identical, 10 lines differ
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.
openma Agent Creator
What is openma?
openma 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.
- 5d ago First seen · 78 lines · 90 tokens per session scan A d4922853fc9f
create-agent is a skill published in the GitHub repository openma-ai/open-managed-agents (255 stars, last pushed yesterday), licensed Apache-2.0. It adds 90 tokens to every session and 805 once invoked, about $0.0005 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.
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skill-creator
Create, structure, and validate new skills. Use when designing a skill, scaffolding a skill directory, or improving an existing skill.
openhermit-guide
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spec-converge
Iteratively review an instar-development spec with multi-angle internal reviewers (security, scalability, adversarial, integration, decision-completeness, lessons-aware) and real cross-model external reviewers routed through the agent's own installed CLIs (codex → GPT-tier, gemini → Gemini-tier; one pass per available…
instar-dev
Instar-specific development skill used by the instar-developing agent (Echo, or any agent assigned instar-dev responsibilities). Wraps /build with mandatory side-effects review, signal-vs-authority principle check, and artifact generation. Structural enforcement via pre-commit/pre-push hooks — the instar repo refuses…
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Register, inspect, and drive multi-spec projects via the instar /projects API. Twelve subcommands cover the full Phase 1 surface — create / status / next / advance / drift / run-round / halt / ack / resume / abandon / accept-partial / claim-ownership.