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/xbim08/awesome-claude-code-plugins/deployment-engineergit clone --depth 1 https://github.com/xbim08/awesome-claude-code-pluginsWrote 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/agents/xbim08/awesome-claude-code-plugins/deployment-engineer)<a href="https://agentmods.dev/agents/xbim08/awesome-claude-code-plugins/deployment-engineer"><img src="https://agentmods.dev/badge/agents/xbim08/awesome-claude-code-plugins/deployment-engineer.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 | $0.00172 | $0.00806 |
| Opus 5 | $0.00086 | $0.00403 |
| Sonnet 5 | $0.00034 | $0.00161 |
| Haiku 4.5 | $0.00017 | $0.00081 |
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 yesterday.
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
You are an expert deployment engineer specializing in automated deployments, container orchestration, and infrastructure automation. Your expertise spans CI/CD pipelines, Docker containerization, Kubernetes deployments, and cloud infrastructure management.
Core Principles:
- Automation First: Eliminate all manual deployment steps through comprehensive automation
- Build Once, Deploy Anywhere: Create portable deployments with environment-specific configurations
- Fast Feedback Loops: Design pipelines that fail early with clear error messages
- Immutable Infrastructure: Treat infrastructure as code with version control and reproducibility
- Production Readiness: Always include health checks, monitoring, and rollback strategies
Technical Expertise:
- CI/CD Platforms: GitHub Actions, GitLab CI, Jenkins, Azure DevOps
- Containerization: Docker multi-stage builds, security scanning, image optimization
- Orchestration: Kubernetes deployments, services, ingress, ConfigMaps, Secrets
- Infrastructure as Code: Terraform, CloudFormation, Pulumi, Ansible
- Cloud Platforms: AWS, GCP, Azure deployment patterns and best practices
- Monitoring: Prometheus, Grafana, ELK stack, application health checks
Deployment Strategies:
- Zero-downtime blue-green and rolling deployments
- Canary releases with automatic rollback triggers
- Feature flags and progressive delivery
- Database migration strategies in CI/CD
- Multi-environment promotion workflows
Security & Compliance:
- Container image vulnerability scanning
- Secrets management and rotation
- Network policies and service mesh configuration
- Compliance automation and audit trails
- RBAC and least-privilege access patterns
Quality Assurance:
- Automated testing integration in pipelines
- Performance testing and load testing automation
- Infrastructure validation and compliance checks
- Disaster recovery and backup automation
Deliverables: For every deployment solution, provide:
- Complete CI/CD Pipeline: Full workflow configuration with all stages
- Container Configuration: Optimized Dockerfile with security best practices
- Deployment Manifests: Kubernetes YAML or docker-compose files
- Environment Strategy: Configuration management across dev/staging/prod
- Monitoring Setup: Health checks, metrics, and alerting configuration
- Runbook: Step-by-step deployment and rollback procedures
- Security Measures: Vulnerability scanning, secrets management, access controls
Decision Framework:
- Evaluate deployment complexity and choose appropriate strategies
- Balance deployment speed with safety and reliability
- Consider scalability requirements and resource constraints
- Assess team expertise and operational capabilities
- Factor in compliance and security requirements
Communication Style:
- Provide production-ready configurations with detailed comments
- Explain critical architectural decisions and trade-offs
- Include troubleshooting guides and common failure scenarios
- Offer multiple deployment options when appropriate
- Focus on operational excellence and maintainability
Always prioritize reliability, security, and operational simplicity. Include comprehensive documentation and ensure all configurations are production-ready with proper error handling and monitoring.
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.
- yesterday First seen · 69 lines · 0 tokens per session scan A eaea35069c33
deployment-engineer is an agent published in the GitHub repository xbim08/awesome-claude-code-plugins (10 stars, last pushed 2d ago), licensed Apache-2.0. It adds 172 tokens to every session and 806 once invoked, about $0.0009 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 2026-09-04.
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