atelier

Atelier

An atelier is the private workshop or studio where a principal master and a number of assistants, students, and apprentices can work together producing fine art or visual art released under the master's name or supervision.

Wikipedia

A personal development toolkit for AI agents - spec-driven development, code quality, deep thinking, and ecosystem patterns.

Skills

This repository includes 34 skills that can be installed via skills.sh. Skills are modular, auto-invoked capabilities that enhance AI agents with specialized knowledge and workflows.

Installing Skills

# Install all skills from the repository
npx skills add martinffx/atelier

# Install specific skills
npx skills add martinffx/atelier --skill typescript:drizzle-orm
npx skills add martinffx/atelier --skill python:fastapi
npx skills add martinffx/atelier --skill spec:research

Available Skills

Spec-Driven Development

• spec:finish - Post-implementation validation
• spec:implement - Execute tasks from plan.json
• spec:plan - Implementation plan + tasks → plan.json
• spec:research - Discovery + research + architecture → spec.md
• spec:orchestrator - Skill routing and workflow orchestration

Deep Thinking

• oracle:architect - DDD patterns, component responsibilities
• oracle:challenge - Critical thinking and challenging approaches
• oracle:testing - Stub-driven TDD and layer boundary testing
• oracle:thinkdeep - Extended sequential reasoning for complex problems

TypeScript Patterns

• typescript:api-design - REST API resource naming, HTTP methods, error responses, pagination
• typescript:drizzle-orm - Type-safe SQL for PostgreSQL/MySQL/SQLite/Cloudflare D1
• typescript:dynamodb-toolbox - Single-table design, entity definitions, GSI patterns
• typescript:fastify - Fastify + TypeBox route handlers and validation
• typescript:functional-patterns - ADTs, branded types, Option/Result, migration guide
• typescript:effect-ts - Functional effects, error handling, resources, schema, services
• typescript:build-tools - Bun, Vitest, Biome, Turborepo configurations
• typescript:testing - Mocking, MSW, snapshot testing

Python Patterns

• python:architecture - Functional core/imperative shell, DDD patterns, layered architecture
• python:fastapi - Pydantic validation, dependency injection, OpenAPI
• python:sqlalchemy - ORM patterns, queries, async, upserts
• python:temporal - Workflow orchestration, activities, error handling
• python:modern-python - Type hints, generics, async/await, pattern matching
• python:monorepo - uv workspaces, mise task orchestration, apps/packages
• python:testing - Stub-Driven TDD, layer boundary testing, pytest patterns
• python:build-tools - uv, mise, ruff, basedpyright, pytest configurations

Skills are auto-invoked based on their description when you work with relevant technologies. No commands needed - just install and AI agents will use them when appropriate.

How Skills Work

Skills are auto-invoked based on context. When you say "create a spec for user auth", the AI matches this to spec:research and loads it automatically.

Namespace Philosophy

Skills are organized into three namespaces based on their role:

Namespace	Type	Invocation	Output	Flexibility
spec:	Workflow	User/previous skill	Artifact	Follow exactly
oracle:	Thinking	Context-driven	Guidance	Adapt to context
code:	Utility	User	Result	Use as needed

• spec: - Sequential workflow steps that produce artifacts
• oracle: - Analytical skills that provide patterns and principles
• code: - Tools and utilities for specific tasks

The Spec Workflow

graph LR
    A[spec:research] -->|spec.md| B[spec:plan]
    B -->|plan.json| C[spec:implement]
    C --> D[spec:finish]
    
    B -.->|design flaw| A
    C -.->|missing tasks| B
    C -.->|fundamental issue| A
    D -.->|bugs found| C

Standard flow:

1. Research - Discovery + research + architecture → spec.md
2. Plan - Break into tasks → plan.json
3. Implement - Execute with TDD
4. Finish - Validate and review

Iteration is normal - Backflows (dotted lines) are expected when:

• Planning reveals design flaws → back to research
• Implementation finds missing tasks → update plan
• Validation finds bugs → back to implement

When to Use Which Skill