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 Omar-Obando/qwen-orchestrator --skill qwen-agentgit clone --depth 1 https://github.com/Omar-Obando/qwen-orchestratorWrote 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/omar-obando/qwen-orchestrator/qwen-agent)<a href="https://agentmods.dev/skills/omar-obando/qwen-orchestrator/qwen-agent"><img src="https://agentmods.dev/badge/skills/omar-obando/qwen-orchestrator/qwen-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/omar-obando/qwen-orchestrator/qwen-agent"><img src="https://agentmods.dev/badge/skills/omar-obando/qwen-orchestrator/qwen-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 | $0.00063 | $0.03417 |
| Opus 5 | $0.00032 | $0.01708 |
| Sonnet 5 | $0.00013 | $0.00683 |
| Haiku 4.5 | $0.00006 | $0.00342 |
Grade A, and why
qwen-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 8d 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 — 512 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Qwen Agent Skill — Qwen Model Integrations & Agent Development
Overview
This skill provides comprehensive guidance for developing Qwen-specific agents, implementing Qwen model integrations, optimizing Qwen performance, and building agent workflows with Qwen models. It includes Qwen API, Qwen-Plus, Qwen-Turbo, and best practices. Based on Qwen official documentation and agent development best practices.
When to Use
Use this skill when:
- Developing Qwen-specific agents
- Implementing Qwen model integrations (Qwen-Turbo, Qwen-Plus, Qwen-Max, Qwen-VL)
- Optimizing Qwen performance and cost management
- Building agent workflows with Qwen models
- Using Qwen API endpoints (DashScope API)
- Configuring Qwen model parameters (temperature, max_tokens, top_p)
- Implementing Qwen chat completions
- Setting up Qwen streaming responses
- Building agents with tools and capabilities
- Implementing Qwen memory and conversation history
- Creating Qwen agents with external knowledge sources
- Building multi-step reasoning with Qwen
- Using Qwen embeddings for semantic search
- Implementing Qwen agent tracing with LangSmith
- Building agents with context window management
- Creating agents with tool calling capabilities
- Implementing retry and error handling for Qwen API
- Setting up rate limiting for Qwen API calls
- Managing Qwen API costs and usage
- Building agents with multimodal capabilities (Qwen-VL)
Do NOT use this skill when:
- Building stateful workflows with complex state (use langgraph skill)
- Designing database schema (use database-design skill)
- Creating UI components (use frontend-design skill)
- Using other LLM providers (use llm-integrations skill)
- Managing agent teams and coordination (use agent-task-coordinator skill)
- Building LangChain-based agents (use langchain skill)
- Implementing complex multi-agent graph architectures (use langgraph skill)
Why avoid: Qwen Agent is specific to Qwen models. For multi-provider support or LangChain integration, use other skills.
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.
- 8d ago First seen · 512 lines · 63 tokens per session scan A 54f860443ab8
qwen-agent is a skill published in the GitHub repository Omar-Obando/qwen-orchestrator (49 stars, last pushed 2mo ago), licensed MIT. It adds 63 tokens to every session and 3,417 once invoked, about $0.0003 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 2026-09-03.
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