GitHub Patterns Marketplace

Production-grade marketplace for repository governance assets, Copilot agents, issue strategy templates, and CI baselines.

Designed to bootstrap and evolve repositories with the GitHub 100% governance model—from collaboration setup to security and AI-assisted operations.

Table of Contents

• Overview
• Quick Start
• Core Concepts
• What Is Included
• Governance Phases (A–E)
• Issue Strategy Catalog
• Registry and Schema
• Validation and Quality Checks
• Real-World Scenarios
• AI Operating Model
• Extending the Marketplace
• Repository Structure
• Contributing
• Roadmap

Overview

GitHub Patterns Marketplace provides reusable, composable assets to standardize repository operations.

Primary goals:

• Accelerate onboarding with consistent governance defaults.
• Improve maintainability through structured templates and machine-readable metadata.
• Enable AI-assisted repository management using specialized Copilot agents.
• Keep the system language-agnostic while supporting stack-aware recommendations.

Quick Start

New here? Start with Option 1 for fastest onboarding, then use Option 2 for fine-grained customization.

Option 1: Copilot Chat Bootstrap

Use this prompt in Copilot Chat:

Act as Repo Architect (setup-orchestrator).
Use:
- https://raw.githubusercontent.com/weslleycapelari/github-patterns/main/agents/setup-orchestrator.agent.md
- https://raw.githubusercontent.com/weslleycapelari/github-patterns/main/registry.json
Start onboarding and ask the intake form.

Option 2: Manual Asset Installation

1. Inspect desired assets in registry.json.
2. Resolve source paths using endpoint_base + path.
3. Copy files to target destinations in your repository.
4. Commit with a setup-oriented message, for example:

chore(setup): apply github-patterns baseline

Core Concepts

The marketplace is driven by two source-of-truth files:

• registry.json: catalog of assets, stacks, governance phases, and paths.
• docs/schemas/registry.schema.json: JSON Schema used to validate registry structure.

Automation agents should resolve assets from registry metadata and avoid hardcoded paths.

What Is Included

Agents

• Repo Architect: orchestrates phase-by-phase repository setup.
• Agent Factory: generates high-quality specialist agents.
• Issue Ops Architect: maps team maturity to issue template strategy.

Baseline Assets

• Copilot instruction baseline.
• CONTRIBUTING baseline.
• CI workflow baseline.

Issue Template Strategies

• minimalist
• open-source
• agile-scrum
• kanban-devops
• enterprise-safe
• shape-up

Governance Phases (A–E)

The GitHub 100% governance model is represented in registry core phases:

• Phase A, Collaboration Base: contribution baseline and issue operations foundation.
• Phase B, Merge Governance: repository-level governance orchestration.
• Phase C, CI/CD and Quality: workflow baseline with linting and conditional tests.
• Phase D, Advanced Security: governance-ready foundation for security controls.
• Phase E, Intelligence and MCP: Copilot instructions and agent-driven operations.

Issue Strategy Catalog

Each strategy is optimized for a different operating model:

• minimalist: fast, low-friction issue flow for solo or MVP projects.
• open-source: stronger triage and duplicate prevention for communities.
• agile-scrum: stories, tasks, epics, and definition-of-done discipline.
• kanban-devops: continuous delivery with incident and RFC support.
• enterprise-safe: compliance, auditability, and security remediation workflows.
• shape-up: appetite-based planning with pitches, scopes, and rabbit-hole handling.

Registry and Schema

Files

• registry.json
• docs/schemas/registry.schema.json

Validation

Use a JSON Schema validator compatible with draft 2020-12.

Example using Python:

python - <<'PY'
import json
from jsonschema import Draft202012Validator

with open('registry.json', encoding='utf-8') as f:
    data = json.load(f)
with open('docs/schemas/registry.schema.json', encoding='utf-8') as f:
    schema = json.load(f)

Draft202012Validator(schema).validate(data)
print('VALID')
PY

Validation and Quality Checks

Recommended checks before release:

1. Validate registry against schema.
2. Verify YAML syntax for all issue templates and workflows.
3. Confirm each registry path maps to an existing file.
4. Ensure all agents and user-facing docs are internally consistent.

Real-World Scenarios

Use the scenario indexes below for quick access:

• Scenario 1 (Laravel + Vue.js 3): docs/en/examples/elite-shop/README.md
• Scenario 2 (Python + FastAPI): docs/en/examples/swift-booking/README.md
• Scenario 3 (React + TypeScript): docs/en/examples/enterprise-admin-panel/README.md

Scenario 1: High-Performance E-Commerce (Laravel + Vue.js 3)

Description: Marketplace with shopping cart, inventory management, and secure checkout.

Technical context: Modular monolith with Laravel 11, Service Layer, Vue 3 Composition API, PostgreSQL with query-level optimization via specialist subagents.

Requirements: Sanctum auth, Pinia state management, FormRequest validation, Pest + Vitest test coverage, N+1 and XSS protection.

Step-by-step documentation:

• Execution index: README.md
• Step 1 (Repo Architect onboarding): 01-onboarding-repo-architect.md
• Step 2 (Issue strategy / Agile-Scrum): 02-issue-ops-architect.md
• Step 3 (Nested delegation with Laravel specialist): 03-laravel-expert-delegacao.md
• Step 4 (ProductService with TDD and standards): 04-product-service-tdd.md

Extended MVP prompt pack (Laravel 13.8 + Blade/Alpine variant):

• Prompt 01 — Factories + Seeders: 05-mvp-factories-seeders.md
• Prompt 02 — Order module: 06-mvp-order-module.md
• Prompt 03 — HTTP API layer: 07-mvp-http-api.md
• Prompt 04 — Frontend Blade + Tailwind + Alpine: 08-mvp-frontend-blade.md
• Prompt 05 — Quality, CI/CD, docs and deploy readiness: 09-mvp-quality-deploy.md

Note: Scenario 1 base context remains Laravel + Vue.js 3. The extended pack documents an alternate Blade-first storefront execution track.

Scenario 2: Hotel Reservation System (Python + FastAPI)

Description: Room booking platform with real-time availability and payment integration.

Technical context: Python 3.11, FastAPI, SQLAlchemy, Alembic migrations, OpenAPI documentation.

Requirements: Layered architecture (Schemas, Models, CRUD, Endpoints), 100% type hints, transaction-safe concurrency, CI quality gates.

Step-by-step documentation:

• Execution index: README.md
• Step 1 (Onboarding and initial governance): 01-onboarding-governance.md
• Step 2 (Phase B branch protection): 02-phase-b-branch-protection.md
• Step 3 (Project audit for transactions and race conditions): 03-project-audit.md

Extended prompt pack:

• Prompt 01 — Domain model + Alembic baseline: 04-domain-model-alembic.md
• Prompt 02 — Availability search API: 05-availability-search-api.md
• Prompt 03 — Reservation workflow API: 06-reservation-workflow-api.md
• Prompt 04 — Concurrency hardening: 07-concurrency-hardening.md
• Prompt 05 — Quality, OpenAPI, and CI gates: 08-quality-openapi-ci.md

Note: the original Scenario 2 centers on onboarding, branch protection, and audit. The extended pack adds an implementation-and-quality track.

Scenario 3: Enterprise Admin Panel (React + TypeScript)

Description: Corporate data dashboard with multi-level access control and data compliance.

Technical context: React 18, TypeScript, Tailwind CSS Design System, React Query, performance monitoring.

Requirements: Phase D (Advanced Security) for PII protection, WCAG 2.2 accessibility, ADR documentation, conventional commit enforcement.

Step-by-step documentation:

• Execution index: README.md
• Step 1 (Governance onboarding + initial ADR): 01-onboarding-governance-adr.md
• Step 2 (Specialist agent creation with Agent Factory): 02-agent-factory-a11y-guardian.md
• Step 3 (Performance-oriented DataChart component): 03-datachart-performance-component.md

Extended prompt pack:

• Prompt 01 — Tailwind design system foundation: 04-design-system-tailwind-foundation.md
• Prompt 02 — React Query data-layer hardening: 05-react-query-data-layer-hardening.md
• Prompt 03 — Phase D PII security hardening: 06-phase-d-pii-security-hardening.md
• Prompt 04 — WCAG 2.2 accessibility audit: 07-wcag-22-accessibility-audit.md
• Prompt 05 — Quality, monitoring, ADRs, and CI: 08-quality-monitoring-adr-commits-ci.md

Note: the original Scenario 3 centers on onboarding, specialist-agent creation, and performance-aware component development. The extended pack adds design-system, security, accessibility, and operational-quality tracks.

AI Operating Model

This repository uses a mandatory AI-first workflow for non-trivial changes.

• Core instructions: .github/copilot-instructions.md
• Specialized governance agents: .github/agents/
• Operational prompts: .github/prompts/
• Error and observability standards: .github/standards/

Required cycle:

1. Develop with a specialist subagent.
2. Review with an independent subagent.
3. Improve and re-validate.

No substantial artifact change should skip the review phase.

Extending the Marketplace

How to add assets and issue strategies

When adding a new asset:

1. Add the file under the correct folder.
2. Register it in registry.json under the appropriate assets section.
3. Update stack recommendations and/or phase mappings if applicable.
4. Update schema only if structure changes.
5. Re-run validation checks.

When adding a new issue strategy:

1. Create strategy folder and config.yml.
2. Add templates with consistent field semantics.
3. Register strategy metadata in assets.issue_strategies.
4. Document expected use case in docs.

Repository Structure

Reference tree

.github/
agents/
docs/
  en/
  pt-br/
  schemas/
library/
  github-baseline/
    issue-templates/
    workflows/
registry.json
README.md

Contributing

Contributions are welcome for:

• New governance assets.
• Improved templates for better human and AI usability.
• Additional stack recommendations.
• Registry/schema hardening and automation.

Please open issues and pull requests with clear scope, rationale, and validation evidence.

Roadmap

Planned improvements

• Expanded Phase D security asset catalog.
• Optional CD deployment baselines.
• Automated registry path integrity checks in CI.
• Additional language-specific setup playbooks.