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.

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

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

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)

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)

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)

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

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

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.

Proactive Skill Usage Summary

Before starting implementation:

• Detect user intent from their message

• Match to skill routing guide above

• Invoke appropriate skill BEFORE writing code

• Follow skill's guided workflow

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

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.