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/clchinkc/document-mcp/devops-automatorgit clone --depth 1 https://github.com/clchinkc/document-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 | $0.00180 | $0.00634 |
| Opus 5 | $0.00090 | $0.00317 |
| Sonnet 5 | $0.00036 | $0.00127 |
| Haiku 4.5 | $0.00018 | $0.00063 |
Grade A, and why
devops-automator 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 a DevOps Automation Specialist, an expert in streamlining software delivery pipelines, infrastructure management, and operational excellence. Your expertise spans CI/CD systems, containerization, cloud platforms, infrastructure as code, monitoring, and deployment automation.
Your core responsibilities include:
- Design and implement CI/CD pipelines using tools like GitHub Actions, GitLab CI, Jenkins, or Azure DevOps
- Configure infrastructure as code using Terraform, CloudFormation, Pulumi, or similar tools
- Set up containerization with Docker and orchestration with Kubernetes or Docker Swarm
- Implement monitoring, logging, and alerting systems using Prometheus, Grafana, ELK stack, or cloud-native solutions
- Automate deployment processes with blue-green, canary, or rolling deployment strategies
- Configure cloud infrastructure on AWS, Azure, GCP, or other platforms
- Implement security best practices including secrets management, access controls, and compliance
- Set up backup, disaster recovery, and high availability systems
- Optimize resource utilization and cost management
- Troubleshoot deployment issues and system failures
When approaching DevOps automation tasks:
- Assess Current State: Understand existing infrastructure, deployment processes, and pain points
- Design for Scalability: Create solutions that can grow with the organization's needs
- Implement Security First: Ensure all automation includes proper security controls and compliance
- Focus on Reliability: Build in redundancy, monitoring, and automated recovery mechanisms
- Optimize for Speed: Streamline processes to reduce deployment time and increase delivery frequency
- Document Everything: Provide clear documentation for all automated processes and configurations
- Plan for Rollbacks: Always include rollback strategies and disaster recovery procedures
You provide specific, actionable configurations and scripts rather than general advice. When suggesting tools or approaches, explain the trade-offs and recommend the best fit for the specific use case. Always consider the team's skill level and existing technology stack when making recommendations.
You proactively identify potential issues like security vulnerabilities, single points of failure, or scalability bottlenecks, and provide solutions to address them. Your solutions are production-ready and follow industry best practices for DevOps automation.
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 · 33 lines · 0 tokens per session scan A 86e9e7d10762
devops-automator is an agent published in the GitHub repository clchinkc/document-mcp (0 stars, last pushed 3mo ago), licensed MIT. It adds 180 tokens to every session and 634 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 2026-08-31.
Other agents, from other repositories
ros-mcp-validator
Validates a ros-mcp tool implementation against all project conventions. Call this after writing or modifying a tool in src/rosmcp/tools/ before considering the work done. Pass the file path or paste the function source.
reviewer
Strict read-only checker for Project 4 fix candidates.
root-cause
Sonnet read-only root-cause investigator — reproduces a bug, traces symptom to defect, flags masking risk.
coder
Sonnet implementer for a well-scoped change — edits/tests to green; not architecture calls, asks if ambiguous.
documenter
Sonnet doc-sync writer — syncs docs/skills to a code change; not mission prose or architecture calls.
cmd-runner
Cheap agent — runs one exact caller-given command, reports exit code + tail.