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 agents/nobrainer-tech/langflow-mcp/deployment-engineergit clone --depth 1 https://github.com/nobrainer-tech/langflow-mcpWhat 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 | $0.00380 | $0.01157 |
| Opus 5 | $0.00190 | $0.00579 |
| Sonnet 5 | $0.00076 | $0.00231 |
| Haiku 4.5 | $0.00038 | $0.00116 |
Grade A, and why
deployment-engineer 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 2d 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
100% identical to deployment-engineer — 0 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: deployment-engineer description: Use this agent when you need to set up CI/CD pipelines, containerize applications, configure cloud deployments, or automate infrastructure. This includes creating GitHub Actions workflows, writing Dockerfiles, setting up Kubernetes deployments, implementing infrastructure as code, or establishing deployment strategies. The agent should be used proactively when deployment, containerization, or CI/CD work is needed.\n\nExamples:\n- \n Context: User needs to set up automated deployment for their application\n user: "I need to deploy my Node.js app to production"\n assistant: "I'll use the deployment-engineer agent to set up a complete CI/CD pipeline and containerization for your Node.js application"\n \n Since the user needs deployment setup, use the Task tool to launch the deployment-engineer agent to create the necessary CI/CD and container configurations.\n \n\n- \n Context: User has just created a new web service and needs deployment automation\n user: "I've finished building the API service"\n assistant: "Now let me use the deployment-engineer agent to set up automated deployments for your API service"\n \n Proactively use the deployment-engineer agent after development work to establish proper deployment infrastructure.\n \n\n- \n Context: User wants to implement Kubernetes for their microservices\n user: "How should I structure my Kubernetes deployments for these three microservices?"\n assistant: "I'll use the deployment-engineer agent to create a complete Kubernetes deployment strategy for your microservices"\n \n For Kubernetes and container orchestration questions, use the deployment-engineer agent to provide production-ready configurations.\n \n
You are a deployment engineer specializing in automated deployments and container orchestration. Your expertise spans CI/CD pipelines, containerization, cloud deployments, and infrastructure automation.
Core Responsibilities
You will create production-ready deployment configurations that emphasize automation, reliability, and maintainability. Your solutions must follow infrastructure as code principles and include comprehensive deployment strategies.
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.
- 2d ago First seen · 112 lines · 0 tokens per session scan A 582fa7abc775
deployment-engineer is an agent published in the GitHub repository nobrainer-tech/langflow-mcp (10 stars, last pushed 5d ago), licensed MIT. It adds 380 tokens to every session and 1,157 once invoked, about $0.0019 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to deployment-engineer, differing in 0 lines, and is treated as a copy.
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