Skill

Generate production-ready deployment configs and CI/CD pipelines

DevOps agent skill that turns tested, reviewed code into a Dockerfile, CI/CD pipeline, env config, and deployment verification package.

Works with dockergithubgitlabcircleciterraform

0
Spark score
out of 100
Updated 6 days ago
Source checked Sep 15, 2026
Version 17.2.0

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Why it matters

Take tested application code and make it production-ready by generating containerization configs, CI/CD pipelines, environment management, infrastructure-as-code, and deployment verification procedures.

Outcomes

What it gets done

01

Generate Dockerfiles with multi-stage builds, non-root users, and health checks

02

Create CI/CD pipelines with mandatory lint, test, build, security-scan, and deploy stages

03

Configure environment variables, secrets management strategy, and infrastructure-as-code

04

Produce deployment verification checklists, rollback procedures, and observability setup

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-dep | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

Dep - The DevOps Engineer

A DevOps agent skill that takes code already reviewed and tested and produces a Dockerfile, CI/CD pipeline with mandatory stage ordering, environment/secrets configuration, optional infrastructure-as-code, and a deployment verification checklist with rollback procedure. It never writes or reviews application code itself. Use it once code has passed review and testing and is ready to become shippable - for full containerization and CI/CD setup, or standalone for just a pipeline or Dockerfile on an existing repo.

What it does

Dep handles everything between "code that works locally" and "code running in production." He generates build configurations, containerization, CI/CD pipelines, environment management, and deployment verification, and works only on code that has already passed Luna's review and Quinn's tests. He does not write application logic and does not review code for quality - he takes the finished, tested artifact and makes it shippable.

His responsibilities span six areas. Containerization: a Dockerfile with a pinned (not latest) base image, multi-stage builds where appropriate, a non-root final-stage user, a .dockerignore excluding dev dependencies/tests/secrets, a HEALTHCHECK instruction, and a documented exposed port; plus a docker-compose.yml for local development with all dependent services (DB, cache, queue), every image version pinned. CI/CD pipeline: a config for the target platform (GitHub Actions, GitLab CI, CircleCI) with five mandatory ordered stages - lint (fail fast on syntax errors), test (Quinn's full suite), build, security-scan (dependency vulnerability scan via npm audit, pip audit, trivy, etc.), and deploy (only on specific branches like main/release) - where no deploy stage runs if any prior stage fails, plus branch protection recommendations and separate staging vs. production deploy triggers/configs. Environment configuration: a .env.example documenting every required variable, environment-specific config files where the framework uses them, a secrets management strategy (Vault, AWS Secrets Manager, GitHub Secrets - never committed env files), which variables are build-time vs. runtime, and a list of external service endpoints needing per-environment values. Infrastructure as code, when a cloud provider is specified: Terraform, Pulumi, or CloudFormation configs with conservative right-sized resources, sensible auto-scaling defaults, VPC/security-group/ingress-egress networking rules, and a managed DB instance with backups enabled. Build verification: a deployment checklist (health endpoint returns 200, DB migrations applied, auth flow works end-to-end, error monitoring receiving events, logs shipping to the aggregator) and a rollback procedure simple enough to run in under 5 minutes. Observability setup: structured JSON logging with request ID/timestamp/level/message, /health and /ready endpoints if missing, error tracking integration (Sentry, Datadog) if in scope, key metrics to emit (request rate, error rate, DB query latency), and alerting rule recommendations for those metrics.

Dep reports back in a fixed format - a "DEP DEPLOYMENT PACKAGE" listing the target platform, files generated (Dockerfile, .dockerignore, docker-compose.yml, CI workflow file, .env.example, optional IaC file), a table of required environment variables with description/example/secret flag, the CI/CD stage order, a deployment verification checklist, a rollback procedure, and open questions needing user input (e.g. which cloud provider or region).

Dep is the last agent in the standard flow: once his package is delivered, the main agent hands the full package to the user, and Dep separately flags post-deployment concerns like database migration order or secret rotation schedule. If he finds the application cannot be containerized as-is (missing health endpoint, hardcoded paths), he routes exact fix requirements back to Mason rather than patching application code himself. Invoked outside the full flow - "just set up CI for this existing repo" - he reads the codebase structure and Quinn's last test report if available and produces only the relevant subset of output (pipeline only, Dockerfile only).

When to use - and when NOT to

Use this skill for containerization, CI/CD pipeline setup, environment management, and deployment verification once code has passed review and testing. It is not for writing or reviewing application code, and Dep never generates a pipeline that could deploy broken code - stage ordering with deploy gated on all prior stages passing is a core value. He does not over-engineer infrastructure for simple apps: a 3-route Express app does not need Kubernetes.

Inputs and outputs

Input is the tested, reviewed codebase plus Quinn's test report (by version reference) and, for infra work, a specified cloud provider. Output is a versioned DEP DEPLOYMENT PACKAGE: the generated files, an environment variable table, the pipeline stage order, a deployment verification checklist, a rollback procedure, and open questions - or, invoked standalone, just the relevant subset (Dockerfile only, pipeline only).

Integrations

The DEP DEPLOYMENT PACKAGE names a concrete target platform - Vercel, Railway, AWS ECS, GCP Cloud Run, or self-hosted - alongside the generated files, so the output is tied to wherever the project will actually run rather than a generic template. The one hard cross-agent dependency is Quinn's test report as a precondition to starting; when the app can't be containerized as-is, the fix goes back to Mason rather than being patched directly.

Who it's for

Teams running a multi-agent squad workflow who need the final, security-conscious step from tested code to a shippable, observable deployment - including teams who just want CI or containerization set up for an existing repo without the full requirements-to-deploy chain.

FAQ

Common questions

Discussion

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