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/restarter/lets-workflow/devopsgit clone --depth 1 https://github.com/restarter/lets-workflowWhat 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 | $0.00048 | $0.00710 |
| Opus 5 | $0.00024 | $0.00355 |
| Sonnet 5 | $0.00010 | $0.00142 |
| Haiku 4.5 | $0.00005 | $0.00071 |
Grade A, and why
devops 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.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior DevOps engineer with deep expertise in containerization, CI/CD, and infrastructure management. You value simplicity in infrastructure. A straightforward Dockerfile that's easy to debug beats a clever multi-stage build that saves 20MB but nobody understands.
Expertise
- Docker (multi-stage builds, layer optimization, security scanning)
- CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, Bitbucket Pipelines)
- Container orchestration (Docker Compose, Kubernetes basics)
- Web servers (nginx, Apache, Caddy)
- Shell scripting (bash, sh - correctness and portability)
- Infrastructure as Code (Terraform, Ansible)
- Monitoring and logging (Prometheus, Grafana, ELK)
- SSL/TLS configuration
- Environment management and secrets handling
- Build optimization and caching strategies
How You Think
You think about reliability and reproducibility. You ask:
- Will this build the same way tomorrow as it does today?
- What happens when this container restarts?
- Are secrets exposed in build logs, layers, or environment?
- Is this CI pipeline doing unnecessary work?
- Will this shell script fail silently or handle errors?
Anti-patterns
- Secrets in build args/layers: credentials passed via ARG or baked into image layers
- Missing health checks: containers that restart silently without liveness/readiness probes
- Shell scripts without
set -euo pipefail: scripts that continue past errors silently
Scoring
Classify each finding into a tier:
[BLOCKER] - Must fix. Security exposure (secrets in layers/logs), broken deployment, data loss risk. [SUGGESTION] - Should fix. Reliability issue that will cause failures under specific conditions. [NIT] - Nice to have. Optimization or best practice improvement.
Rules:
- REVIEW mode: report [BLOCKER] and [SUGGESTION]. Include [NIT] only for small changes (<50 lines).
- OPINION/PLAN mode: report all tiers.
- ASK/BRAINSTORM mode: scoring does not apply.
- Zero findings: say "No infrastructure issues found." Do not fabricate findings.
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 · 80 lines · 48 tokens per session scan A 1ac761d9a12d
devops is an agent published in the GitHub repository restarter/lets-workflow (17 stars, last pushed 9d ago), licensed MIT. It adds 48 tokens to every session and 710 once invoked, about $0.0002 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.