galaxy-context

Galaxy Development Context & Skill Routing

This skill provides essential Galaxy conventions and routing guidance to help you proactively use the right Galaxy skills and agents.

Automatic Skill Invocation - CRITICAL

You should PROACTIVELY invoke Galaxy skills when you detect relevant tasks, without waiting for explicit user requests. Match user intent to skills below.

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Skill Routing Guide

1. Database Operations → /galaxy-db-migration

Invoke when user mentions:

• "database", "schema", "migration", "Alembic"
• "add column", "create table", "modify database", "database version"
• "upgrade database", "downgrade database", "migration error"
• SQL model changes in lib/galaxy/model/__init__.py
• Alembic revision files in lib/galaxy/model/migrations/alembic/versions_gxy/

Examples:

• "I need to add a new table for credentials" → /galaxy-db-migration create
• "How do I add a column to the workflow table?" → /galaxy-db-migration create
• "The database won't upgrade" → /galaxy-db-migration troubleshoot
• "Check if migration is needed" → /galaxy-db-migration status

Actions:

• create - Creating new migrations after model changes
• upgrade - Upgrading database to latest version
• downgrade - Rolling back migrations
• status - Checking database version vs codebase
• troubleshoot - Diagnosing migration errors

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2. API Development → /galaxy-api-endpoint

Invoke when user mentions:

• "API", "endpoint", "REST", "route", "router"
• "FastAPI", "Pydantic", "schema", "request/response model"
• "create endpoint for...", "add API for...", "new endpoint"
• Files in lib/galaxy/webapps/galaxy/api/
• Files in lib/galaxy/schema/

Examples:

• "Create an API endpoint for managing credentials" → /galaxy-api-endpoint credentials
• "I need a REST API for workflows" → /galaxy-api-endpoint workflows
• "Add a new route to handle..." → /galaxy-api-endpoint [resource-name]

Action:

• Always pass the resource name as argument (e.g., /galaxy-api-endpoint credentials)
• Guides through: Pydantic schemas → Manager logic → FastAPI router → Tests

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3. Testing Operations → /galaxy-testing

Invoke when user mentions:

• "test", "tests", "pytest", "run_tests.sh"
• "write tests", "add test", "test this feature"
• "test failure", "test error", "tests are failing"
• "ApiTestCase", "integration test", "unit test", "functional test"
• Files in test/, lib/galaxy_test/

Examples:

• "Run the integration tests" → /galaxy-testing run
• "Write tests for this new API" → /galaxy-testing write
• "How do I test this endpoint?" → /galaxy-testing api
• "The tests are failing" → /galaxy-testing run (to diagnose)

Actions:

• run - Running tests (unit, integration, selenium)
• write - Writing new tests (guides through patterns)
• api - API testing patterns (ApiTestCase, fixtures)

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4. Linting & Formatting → /galaxy-linting

Invoke when user mentions:

• "lint", "linting", "format", "formatting", "code style"
• "ruff", "black", "isort", "flake8", "mypy", "darker", "autoflake", "pyupgrade"
• "eslint", "prettier", "type check", "type error"
• "tox -e lint", "tox -e format", "make format", "make pyupgrade"
• "CI lint", "lint failure", "lint error", "formatting error"
• "fix formatting", "auto-fix", "clean up code style"
• "unused imports", "modernize Python", "remove imports"
• "API schema lint", "config lint", "XSD", "codespell", "redocly"

Examples:

• "Run lint checks" → /galaxy-linting check
• "Fix formatting issues" → /galaxy-linting fix
• "How do I format Python code?" → /galaxy-linting python
• "Type checking errors" → /galaxy-linting mypy
• "Run all CI checks" → /galaxy-linting full
• "Client-side linting" → /galaxy-linting client
• "Remove unused imports" → /galaxy-linting fix
• "Modernize Python syntax" → /galaxy-linting fix
• "Lint API schema" → /galaxy-linting (for specialized targets)

Actions:

• check - Quick lint check (format + lint, fastest feedback)
• fix - Auto-fix formatting (make diff-format, make format, make pyupgrade, autoflake)
• python - Python linting details (ruff, black, isort, flake8, darker, pyupgrade)
• client - Client-side linting (ESLint, Prettier, granular targets)
• mypy - Type checking with mypy
• full - Complete lint suite (all CI checks)
• No argument - For specialized targets (API schema, XSD, config files)

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5. Codebase Architecture Questions → galaxy-explorer Agent

Use Task tool with subagent_type="galaxy-explorer" when user asks:

• "Where is X implemented?"
• "How does Y work?"
• "What's the architecture of Z?"
• "Find the component that handles..."
• "Show me examples of..."
• Broad exploration questions about code structure

Examples:

• "Where is authentication handled?" → Spawn galaxy-explorer
• "How do workflows execute?" → Spawn galaxy-explorer
• "What's the testing structure?" → Spawn galaxy-explorer

Why use galaxy-explorer:

• Knows Galaxy architecture deeply
• Avoids reading large files completely
• Can answer multi-file architectural questions efficiently
• Understands Galaxy conventions and patterns

Do NOT use galaxy-explorer for:

• Specific needle queries (use Grep/Glob directly)
• Reading known file paths (use Read directly)
• Simple file searches (use Glob directly)

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Critical Galaxy Conventions

Testing: ALWAYS use run_tests.sh

NEVER run pytest directly - Galaxy's test suite requires special setup:

# Correct
./run_tests.sh -integration test/integration/test_credentials.py

# Wrong - will fail or miss fixtures
pytest test/integration/test_credentials.py

Why:

• Sets up Galaxy test database
• Configures Galaxy-specific fixtures
• Manages test isolation
• Handles Galaxy configuration

Large Files: NEVER Read Completely

These files will exhaust your token budget if read entirely:

• client/src/api/schema/schema.ts (46,529 lines) - Auto-generated
• lib/galaxy/model/__init__.py (12,677 lines) - Core models
• lib/galaxy/tools/__init__.py (4,857 lines) - Tool framework
• lib/galaxy/schema/schema.py (4,184 lines) - API schemas

Instead:

• Use Grep with specific patterns
• Read with offset/limit to get relevant sections
• Use galaxy-explorer agent for architectural understanding

Manager Pattern

Business logic lives in manager classes:

• Location: lib/galaxy/managers/
• Pattern: {Resource}Manager (e.g., WorkflowsManager)
• Purpose: Separate business logic from API layer

Flow: API Router → Manager → Model

FastAPI Structure

Modern Galaxy API follows FastAPI patterns:

• Routers: lib/galaxy/webapps/galaxy/api/*.py
• Schemas: lib/galaxy/schema/*.py (Pydantic models)
• Tests: lib/galaxy_test/api/test_*.py

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Quick Architecture Reference

Backend (Python)

lib/galaxy/
├── model/                 # SQLAlchemy models
│   └── migrations/       # Alembic migrations
├── managers/             # Business logic (Manager pattern)
├── schema/               # Pydantic API schemas
├── webapps/galaxy/api/   # FastAPI routers
├── tools/                # Tool execution engine
└── workflow/             # Workflow engine

Frontend (Vue.js)

client/src/
├── components/           # Vue components
├── stores/               # Pinia stores
├── composables/          # Composition functions
└── api/                  # API client + generated schemas

Tests

test/
├── unit/                 # Fast unit tests
├── integration/          # Integration tests
└── integration_selenium/ # E2E browser tests

lib/galaxy_test/
└── api/                  # API endpoint tests

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When to Use Each Approach

Parallel Tool Calls

When operations are independent:

Read: lib/galaxy/managers/workflows.py
Read: client/src/stores/workflowStore.ts
Read: test/unit/test_workflows.py

Targeted Searches

For specific patterns in large files:

Grep: pattern="class Workflow\(" path="lib/galaxy/model/__init__.py" output_mode="content" -A=20

Galaxy-Explorer Agent

For understanding architecture or locating functionality across multiple files.

Direct Tool Use

For known file paths or simple operations.

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Proactive Skill Usage Summary

Before starting implementation:

1. Detect user intent from their message
2. Match to skill routing guide above
3. Invoke appropriate skill BEFORE writing code
4. Follow skill's guided workflow

Key principle: Skills prevent mistakes by enforcing Galaxy conventions and best practices. Use them proactively rather than reactively.

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Additional Notes

• Galaxy uses Python 3.9+ with FastAPI, SQLAlchemy 2.0, Celery, Pydantic
• Frontend: Vue.js 2.7 with TypeScript, Pinia, Vite
• Main branch: dev (not main)
• Code style: Black (120 chars), isort, Ruff, mypy with strict mode
• Always use type hints in Python
• Prefer TypeScript over JavaScript for new frontend code
• Linting tools: ruff (lint + format), black, isort, flake8, mypy, autoflake, pyupgrade, ESLint, Prettier
• Specialized linting: codespell, redocly (API schema), xmllint (XSD), config validators
• Quick formatting tip: Use make diff-format during development for fast incremental formatting

This context is optimized for the Galaxy codebase as of January 2026.