App Development logo

App Development

Organization
lubusIN
app-development

Scaffold and architect custom Frappe apps including app structure, hooks, background jobs, service layers, and production hardening. Use when creating new apps, setting up app architecture, or implementing cross-cutting patterns like caching, logging, and error handling.

Overview

PublisherlubusIN
Repositoryfrappe-skills
Skill nameapp-development
Stars
62
Forks
23
Bundled files
28
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 28 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by lubusIN on GitHub. Read the source before you install it.

Installation

Install the App Development AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/lubusIN/frappe-skills.git /tmp/frappe-skills
mkdir -p .claude/skills
cp -r /tmp/frappe-skills/app-development .claude/skills/app-development
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable App Development in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads App Development on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so App Development is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Frappe App Development

Scaffold, structure, and architect custom Frappe applications with production-grade patterns.

When to use

  • Creating a new custom Frappe app from scratch
  • Setting up app architecture (modules, services, utils)
  • Configuring hooks.py for events, scheduler, overrides
  • Implementing background jobs and async processing
  • Building service layers and domain logic patterns
  • Adding caching, logging, error handling utilities
  • Preparing apps for production deployment
  • Managing translations, versioning, and packaging

Inputs required

  • App name and purpose
  • Target Frappe version (v13+, v15+, v16+)
  • Module structure (which DocTypes, APIs, services)
  • Whether hooks/overrides of other apps are needed
  • Background job requirements
  • Production readiness needs

Procedure

0) Scaffold the app

bash
# Create the app
bench new-app my_app

# Install on site
bench --site mysite.local install-app my_app

# Verify developer mode
bench --site mysite.local console
>>> frappe.conf.developer_mode  # Must be True

1) Plan app structure

Follow the domain architecture pattern — keep DocType controllers thin and business logic in service modules:

my_app/
├── my_app/
│   ├── __init__.py
│   ├── hooks.py              # App hooks and configuration
│   ├── api.py                # Public API surface (RPC endpoints)
│   ├── services/             # Business logic modules
│   │   └── billing.py
│   ├── utils/                # Cross-cutting utilities
│   │   ├── cache.py
│   │   ├── errors.py
│   │   ├── logging.py
│   │   ├── permissions.py
│   │   └── validation.py
│   ├── background_jobs/      # Async job handlers
│   │   └── export_job.py
│   ├── integrations/         # External system connectors
│   │   └── payment_gateway.py
│   ├── my_module/
│   │   ├── doctype/
│   │   │   └── my_doc/
│   │   │       ├── my_doc.json
│   │   │       ├── my_doc.py
│   │   │       ├── my_doc.js
│   │   │       └── test_my_doc.py
│   │   ├── report/
│   │   └── dashboard/
│   └── translations/
│       ├── en.csv
│       └── fr.csv
├── setup.py
└── README.md

Use the mini-app-template in assets/mini-app-template/ as a starting scaffold.

2) Configure hooks.py

python
# hooks.py

app_name = "my_app"
app_title = "My App"
app_publisher = "My Company"

# DocType lifecycle events
doc_events = {
    "Sales Order": {
        "on_submit": "my_app.services.billing.on_order_submit",
        "on_cancel": "my_app.services.billing.on_order_cancel",
    },
    "*": {
        "after_insert": "my_app.utils.logging.log_creation",
    }
}

# Scheduled tasks
scheduler_events = {
    "daily": [
        "my_app.background_jobs.cleanup.run_daily_cleanup"
    ],
    "cron": {
        "0 */6 * * *": [
            "my_app.background_jobs.sync.sync_external_data"
        ]
    }
}

# Client-side script injection
doctype_js = {
    "Sales Order": "public/js/sales_order.js"
}

doctype_list_js = {
    "Sales Order": "public/js/sales_order_list.js"
}

# Override another app's controller (use sparingly)
# override_doctype_class = {
#     "ToDo": "my_app.overrides.custom_todo.CustomToDo"
# }

# Extend controller without full replacement (v16+, preferred)
# extend_doctype_class = {
#     "ToDo": "my_app.overrides.todo_extension.TodoExtension"
# }

# Override whitelisted methods
# override_whitelisted_methods = {
#     "frappe.client.get_list": "my_app.overrides.custom_get_list"
# }

3) Implement service layer

Keep DocType controllers thin — delegate business logic to services:

python
# my_app/services/billing.py
import frappe

def on_order_submit(doc, method):
    """Handle order submission — called via doc_events hook."""
    if doc.grand_total > 10000:
        create_approval_request(doc)
    generate_invoice(doc)

def generate_invoice(order):
    """Create invoice from submitted order."""
    invoice = frappe.get_doc({
        "doctype": "Sales Invoice",
        "customer": order.customer,
        "items": [
            {"item_code": i.item_code, "qty": i.qty, "rate": i.rate}
            for i in order.items
        ]
    })
    invoice.insert()
    invoice.submit()
    return invoice

4) Set up background jobs

python
# my_app/background_jobs/export_job.py
import frappe

def enqueue_export(filters):
    """Enqueue a long-running export job."""
    frappe.enqueue(
        "my_app.background_jobs.export_job.run_export",
        filters=filters,
        queue="long",
        timeout=600,
        is_async=True
    )

def run_export(filters):
    """Execute the export — runs in background worker."""
    data = frappe.get_all("Sales Order", filters=filters, fields=["*"])
    # Process data...
    frappe.publish_realtime("export_complete", {"count": len(data)})

5) Add cross-cutting utilities

python
# my_app/utils/cache.py
import frappe

def get_cached_settings(key):
    """Cache expensive settings lookups."""
    value = frappe.cache().get_value(f"my_app:{key}")
    if value is None:
        value = frappe.db.get_single_value("My Settings", key)
        frappe.cache().set_value(f"my_app:{key}", value)
    return value

def invalidate_cache(key):
    frappe.cache().delete_value(f"my_app:{key}")
python
# my_app/utils/errors.py
import frappe

def api_error(message, status_code=400, exc=None):
    """Consistent error response for API endpoints."""
    frappe.local.response["http_status_code"] = status_code
    frappe.throw(message, exc or frappe.ValidationError)

6) Handle translations

python
# In Python code
frappe._("Hello World")   # Mark string for translation

# In JavaScript
__("Hello World")         # Mark string for translation
bash
# Translation CSV files go in my_app/translations/
# e.g., my_app/translations/fr.csv:
# Hello World,Bonjour le monde

7) Version compatibility

FeatureMinimum Version
extend_doctype_classFrappe v16+
REST API v2 (/api/v2/)Frappe v15+
Token-based authFrappe v11.0.3+

When targeting multiple versions, guard version-specific features:

python
import frappe

if hasattr(frappe, 'extend_doctype_class'):
    # v16+ pattern
    pass
else:
    # Fallback for older versions
    pass

Verification

  • App installs without errors: bench --site <site> install-app my_app
  • Hooks fire correctly (check scheduler logs, doc events)
  • Background jobs enqueue and complete
  • bench --site <site> migrate succeeds
  • Tests pass: bench --site <site> run-tests --app my_app

Failure modes / debugging

  • App not found: Check apps.txt and sites/<site>/site_config.json
  • Hooks not firing: Verify hooks.py syntax; restart bench
  • Background jobs stuck: Check worker status with bench doctor; verify Redis
  • Import errors: Ensure module paths in hooks match actual Python paths
  • Developer mode off: DocType changes won't export to files

Escalation

  • For DocType creation details → doctype-development
  • For API endpoint patterns → api-development
  • For Desk UI customization → desk-customization
  • For Frappe UI frontends → frontend-development
  • For print formats and Jinja → printing-templates
  • For reports → reports
  • For web forms → web-forms
  • For testing → testing
  • For enterprise architecture → enterprise-patterns
  • For Docker/FM environments → frappe-manager

References

Cross-references (owned by specialized skills)

Guardrails

  • Use Frappe UI for custom frontends: Never use vanilla JS, jQuery, or custom frameworks. Frappe UI (Vue 3 + TailwindCSS) is the ecosystem standard. See frontend-development for setup.
  • Follow CRM/Helpdesk patterns for CRUD apps: Follow ui-patterns skill for app shell, navigation, list views, and form layouts derived from official Frappe apps.
  • Follow naming conventions: App name must be lowercase with underscores, valid Python identifier
  • Use hooks.py for integrations: Never monkey-patch; use doc_events, scheduler_events, boot_session hooks
  • Keep hooks.py clean: Only configuration, no logic; import from modules
  • Maintain backwards compatibility: Use frappe.version checks for cross-version support
  • Export fixtures properly: Use fixtures in hooks.py for data that should sync with app

Common Mistakes

MistakeWhy It FailsFix
App not in installed_appsApp code not loadedRun bench --site <site> install-app my_app
Wrong module path in hooksEvents don't fireVerify path matches actual my_app/module/file.py structure
Duplicate hook registrationsEvents fire multiple timesCheck hooks.py for duplicates; use list not repeated keys
Editing hooks.py without restartChanges not picked upRun bench restart after hooks.py changes
Missing __init__.py filesModule import errorsEnsure every directory has __init__.py
Logic in hooks.pyHard to test, import errorsMove logic to separate modules, import in hooks
Building frontend with vanilla JS/jQueryInconsistent with ecosystemUse Frappe UI (Vue 3); see frontend-development
Custom app shell for CRUD appsInconsistent UXFollow CRM/Helpdesk patterns for navigation and layouts

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the App Development AI skill do?

Scaffold and architect custom Frappe apps including app structure, hooks, background jobs, service layers, and production hardening. Use when creating new apps, setting up app architecture, or implementing cross-cutting patterns like caching, logging, and error handling.

Why use App Development on TypingMind?

Because you install it once and use it with any model. App Development is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install App Development in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lubusIN/frappe-skills/tree/main/app-development. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use App Development?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with App Development?

As many as you like. As long as a model supports skills, you can use App Development with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the App Development AI skill free?

Yes. It is published on GitHub by lubusIN under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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