SeedScaffold is a composable toolchain that generates the infrastructure every service needs — API docs, CI/CD, monitoring, test suites, database migrations — from a single unified CLI. Standard library only. No install footprint.
# scaffold the full toolchain into an existing service skill run --preset full-stack \ --project /data/projects/m9410_UserService \ --service-name "UserService" --service-port 9410 ✓ api-docs OpenAPI spec + Swagger UI ✓ cicd GitHub Actions / GitLab CI + Dockerfile ✓ monitoring Prometheus + Grafana dashboards ✓ testing Jest / Playwright test suite ✓ database migrations + ORM models ✓ performance profiling dashboard ✓ quality code-quality report
Run a skill on its own or compose several through a preset. Each one inspects your project and writes ready-to-use configuration — no boilerplate to hand-copy.
Produces an OpenAPI specification and a browsable Swagger UI site for your services.
Generates CI/CD configuration for GitHub Actions or GitLab CI, plus Dockerfile and k8s manifests.
Creates a Prometheus + Grafana monitoring setup wired to the services you name.
Scaffolds a Jest or Playwright test framework so new projects start with a testing baseline.
Generates migration scripts and ORM models for your chosen database and ORM.
Capture a project as a reusable template, then apply it to spin up new services.
Builds a performance-analysis dashboard for the services under review.
Runs code-quality checks and produces a report you can drop into review.
These eight are the production tool skills wired into the built-in presets. The repository also carries additional experimental generators; run skill list to see what is installed in your copy.
A preset is an ordered bundle of skills. Pick one instead of chaining commands by hand — or copy a preset JSON and tailor your own.
No package to install — SeedScaffold runs on the Python standard library. Alias the CLI and go.
# 1. set up the CLI alias cd /data/projects/m488_SeedScaffold alias skill='python3 skill_cli.py' # 2. see what is available skill list skill presets # 3. initialize a new project on a chosen port skill init my-new-project --port 9500 # 4. add a single skill to an existing project skill add api-docs --project /data/projects/m9410_UserService # 5. or run a whole preset at once skill run --preset minimal --project /data/projects/m9410_UserService
Prefer a global command? Symlink skill_cli.py onto your PATH. Every skill also runs standalone via python3 skills/<name>_skill.py --help.
Run the full-stack preset the moment a service is created so it ships with docs, pipelines, monitoring and tests from day one.
Point the devops or quality preset at a running project to backfill the operational infrastructure it never got.
Capture a reference project as a template, then apply it across services so every repo follows the same conventions.
Every skill inherits the same integration base, so the CLI, parameters and output layout stay predictable as the library grows.
Pass a project path, service name and port. The skill reads what is there.
Each skill writes ready-to-use configuration and artifacts into place.
Presets run skills in a defined order, skipping steps that lack params.
Copy the integration template, subclass, and add your own skill.
Alias the CLI, run a preset, and let SeedScaffold generate the scaffolding for you.