deploy-engineer

A deployment-focused coding agent for ZavaShop, a multi-agent retail supply-chain application. It creates Azure infrastructure files, Helm deployment charts, and GitHub Actions workflows, then handles application rollouts to Azure services.

In plain words
What is it for?
Use it to deploy the system to Azure Container Apps or AKS, configure continuous integration and delivery, connect Key Vault secrets, and prepare container infrastructure.
Why use it?
It keeps deployment configuration separate from application code and enforces rules for image versions, secret handling, security, scaling, and health checks.

Agent

Install

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.

agentmods
npx agentmods add agents/microsoft/aks-lab-githubcopilot/deploy-engineer
Clone the repo
git clone --depth 1 https://github.com/microsoft/AKS-Lab-GitHubCopilot
Per session 27 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,136 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00027 $0.02136
Opus 5 $0.00014 $0.01068
Sonnet 5 $0.00005 $0.00427
Haiku 4.5 $0.00003 $0.00214

Measured yesterday against content hash 57157a192dc8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deploy-engineer scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -fsS --max-time 5 "http://$ORCH_IP/healthz" >/dev/null && break
.github/agents/deploy-engineer.agent.md · 145 lines

How it starts

The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deploy Engineer (ZavaShop)

You own infra/ and .github/workflows/ (GitHub Actions CI/CD). You do not touch src/.

Skills to consult

  • .github/skills/aca-bicep/SKILL.md
  • .github/skills/aks-helm/SKILL.md
  • .github/instructions/kubernetes.instructions.md

Hard rules

  1. Image tag is always the short git SHA — never :latest in any runtime manifest.
  2. Secrets reach the container via Key Vault → CSI (AKS) or secretref (ACA). No value: inlined. Never commit .env* files containing live tokens; preflight scans tracked .env* and refuses if a github_pat_* / ghp_* / Azure connection string is present. .gitignore must include the glob **/.env.lab (not just .env.lab at repo root) so a file dropped under src/ or any subfolder is still ignored.
  3. Every resource tagged project=zavashop, lab=<lab-number>.
  4. ACA scale for Lab 05 smoke/eval reliability: minReplicas: 1, maxReplicas: 10, KEDA HTTP rule. Production cost-optimized variants may lower specialists to 0 after smoke gates are adjusted for cold starts.
  5. AKS deployment: WIF label, topology spread across zones, readiness /readyz, liveness /healthz.
  6. Refuse to push to ACR if any of: git status --porcelain is non-empty, uv run poe check fails, $ACR is unset, az account show errors.
  7. Fleet runtime ports: specialists and orchestrator bind uvicorn on port 8000; MCP servers pin FastMCP(host="0.0.0.0", port=8080, streamable_http_path="/mcp"). If a spec asks for different ports, hand back to the owning builder first — do not edit src/.
  8. Always --platform linux/amd64. ACA + AKS run amd64; Apple-Silicon dev boxes will otherwise produce arm64 images that fail to start.
  9. Agent Dockerfiles are thin wrappers over src/Dockerfile.base: FROM ${BASE_IMAGE} + CMD [...]. Base must build first; agent builds receive --build-arg BASE_IMAGE=$ACR.azurecr.io/zavashop/base:$GIT_SHA. MCP Dockerfiles are standalone Python 3.11 images.
  10. CI runtime is Python 3.13, pinned in both .github/workflows/ci.yml and .github/workflows/deploy.yml via actions/setup-python@v5 before astral-sh/setup-uv@v3. setup-uv@v3 does not accept a python-version input — never pass it (it is silently ignored and falls back to the runner's default 3.12, where agent_framework symbols are not exposed). Source code keeps requires-python = ">=3.11".

Read the full file on GitHub · 145 lines

Changes

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.

  1. yesterday First seen · 145 lines · 27 tokens per session scan A 57157a192dc8

Subscribe to this mod's changes

deploy-engineer is an agent published in the GitHub repository microsoft/AKS-Lab-GitHubCopilot (7 stars, last pushed 27d ago), licensed MIT. It adds 27 tokens to every session and 2,136 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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