> Generate SaaS boilerplate with auth, database schemas, Stripe billing, multi-tenancy, API routes, and dashboard UI on a Next.js/TypeScript/Tailwind stack. Use when starting a new SaaS product, subscription app, or multi-tenant platform.
npx skills add https://github.com/borghei/Claude-Skills --skill saas-scaffolder
Generate a complete, production-ready SaaS application boilerplate including authentication (NextAuth, Clerk, or Supabase Auth), database schemas with multi-tenancy, billing integration (Stripe or Lemon Squeezy), API routes with validation, dashboard UI with shadcn/ui, and deployment configuration. Produces a working application from a product specification in under 30 minutes.
Keywords: SaaS, boilerplate, scaffolding, Next.js, authentication, Stripe, billing, multi-tenancy, subscription, starter template, NextAuth, Drizzle ORM, shadcn/ui
.env.example, schema, and API routes for a Next.js stack.Before scaffolding, confirm these inputs. If any is unknown or vague, ASK — do not assume:
--auth; changes the auth config and middleware generated)--payments; determines the billing + webhook handler)--tenancy; shapes the entire database schema and scoped queries)--db; sets the Drizzle adapter and connection config)Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
| Tool | Purpose | Command |
|------|---------|---------|
| saas_scaffolder.py | Generate a production-ready SaaS project structure (auth, billing, tenancy) | python scripts/saas_scaffolder.py --name my-saas --auth nextauth --db neondb --payments stripe --tenancy workspace |
| feature_flag_manager.py | CRUD + evaluate feature flags on a JSON store | python scripts/feature_flag_manager.py evaluate --key dark-mode --environment production --plan pro |
| tenant_config_validator.py | Validate multi-tenant config and scan source for missing tenant scoping / isolation issues | python scripts/tenant_config_validator.py --config tenant_config.json --src ./app |
Load the reference that matches the task — keep this file lean and pull detail on demand:
.env.example variables. Read when defining the spec, laying out files, or writing the schema/env config.This skill covers:
This skill does NOT cover:
stripe-integration-expertdatabase-schema-designerci-cd-pipeline-builderapi-design-reviewer| Skill | Integration | Data Flow |
|-------|-------------|-----------|
| stripe-integration-expert | Extends the scaffolded Stripe setup with advanced billing patterns (metered, tiered, usage-based) | Scaffolder outputs base Stripe config and webhook handler; Stripe expert refines pricing models and adds invoice customization |
| database-schema-designer | Designs extended schemas beyond the core tenancy tables | Scaffolder provides baseline users/workspaces/members schema; schema designer adds domain-specific entities and optimizes indexes |
| api-design-reviewer | Reviews and improves the generated API routes for consistency and standards compliance | Scaffolder generates initial API routes; reviewer audits naming, error handling, and response formats |
| ci-cd-pipeline-builder | Creates deployment pipelines for the scaffolded project | Scaffolder outputs the application code; pipeline builder adds GitHub Actions, preview deployments, and production release workflows |
| env-secrets-manager | Audits and secures the environment variable configuration | Scaffolder generates .env.example; secrets manager validates no secrets are hardcoded and recommends vault integration |
| observability-designer | Adds logging, tracing, and monitoring to the scaffolded application | Scaffolder provides the application structure; observability designer instruments API routes, webhooks, and auth flows |
Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
Fast CLI/Python queries to 20+ bioinformatics databases. Use for quick lookups: gene info, BLAST searches, AlphaFold structures, enrichment analysis. Best for interactive exploration, simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications. Use when: bullmq, bull queue, redis queue, background job, job queue.
Create custom external web service APIs for Moodle LMS. Use when implementing web services for course management, user tracking, quiz operations, or custom plugin functionality. Covers parameter validation, database operations, error handling, service registration, and Moodle coding standards.
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
Take borghei/saas-scaffolder from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.