Frappe Ops App Lifecycle logo

Frappe Ops App Lifecycle

Organization
Impertio-Studio
frappe-ops-app-lifecycle

Use when scaffolding a new Frappe app, configuring app settings, building assets, running tests, deploying, updating, or publishing to marketplace. Prevents broken app structure from incorrect scaffolding, missing setup.py fields, and failed builds. Covers bench new-app, app directory structure, setup.py/pyproject.toml, hooks.py config, bench build, bench run-tests, app publishing. Keywords: app lifecycle, new-app, scaffolding, setup.py, pyproject.toml, hooks.py, bench build, app publishing, marketplace, create app, publish app, app structure, how to start new app, app directory layout..

Overview

PublisherImpertio-Studio
RepositoryFrappe_Claude_Skill_Package
Skill namefrappe-ops-app-lifecycle
Stars
180
Forks
53
Bundled files
4
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.

  • 4 bundled files

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

  • Open source

    Published by Impertio-Studio on GitHub. Read the source before you install it.

Installation

Install the Frappe Ops App Lifecycle 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/Impertio-Studio/Frappe_Claude_Skill_Package.git /tmp/Frappe_Claude_Skill_Package
mkdir -p .claude/skills
cp -r /tmp/Frappe_Claude_Skill_Package/skills/source/ops/frappe-ops-app-lifecycle .claude/skills/frappe-ops-app-lifecycle
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Frappe Ops App Lifecycle 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 Frappe Ops App Lifecycle 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 Frappe Ops App Lifecycle 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.

App Lifecycle Management

Quick Reference

CommandPurposeWhen to Use
bench new-appScaffold new appStarting a new project
bench get-app URLClone from GitInstalling existing app
bench --site SITE install-appInstall on siteAfter get-app or new-app
bench --site SITE remove-appUninstall from siteRemoving app from site
bench remove-appRemove from benchRemoving app entirely
bench --site SITE migrateRun patches + syncAfter code changes
bench buildCompile assetsAfter JS/CSS changes
bench --site SITE consolePython REPLDebugging
bench startStart dev serverDevelopment
bench setup productionConfigure nginx+supervisorDeploying to production

1. Scaffolding: bench new-app

bash
bench new-app my_custom_app

Interactive prompts:

  • App Title → Human-readable name
  • App Description → One-line summary
  • App Publisher → Company/author name
  • App Email → Contact email
  • App Icon → Default: octicon octicon-file-directory
  • App Color → Default: grey
  • App License → Default: MIT

Generated Directory Structure

apps/my_custom_app/
├── MANIFEST.in              # Files included in Python package
├── README.md                # Project readme
├── license.txt              # License file
├── requirements.txt         # Python dependencies
├── dev-requirements.txt     # Dev-only Python deps (v15+)
├── package.json             # Node.js dependencies
├── setup.py                 # Python package config (v14)
├── pyproject.toml           # Python package config (v15+)
├── my_custom_app/
│   ├── __init__.py          # App version string
│   ├── hooks.py             # Framework integration hooks
│   ├── modules.txt          # List of app modules
│   ├── patches.txt          # Migration patches list
│   ├── config/
│   │   ├── __init__.py
│   │   ├── desktop.py       # Desktop/workspace config
│   │   └── docs.py          # Documentation config
│   ├── public/              # Static assets → /assets/my_custom_app/
│   │   ├── css/
│   │   └── js/
│   ├── templates/           # Jinja templates
│   └── www/                 # Portal pages (URL = path)

What Each Core File Does

FilePurposeNEVER Forget
__init__.pyDefines __version__ALWAYS update before release
hooks.pyALL framework integrationEntry point for everything
modules.txtDeclares app modulesALWAYS add new modules here
patches.txtMigration patch registryALWAYS add patches in order
requirements.txtPython deps installed on setupAdd pip packages here
public/Static files served by nginxAccessible at /assets/app_name/
www/Portal pagesFilename = URL path

2. Development Cycle

Code → Migrate → Build → Test → Commit

Step-by-Step

bash
# 1. Make code changes (DocTypes, reports, APIs, etc.)

# 2. Migrate — sync DocType schema + run patches
bench --site mysite migrate

# 3. Build — compile JS/CSS assets
bench build --app my_custom_app

# 4. Test — run Python tests
bench --site mysite run-tests --app my_custom_app

# 5. Commit
git -C apps/my_custom_app add -A && git -C apps/my_custom_app commit -m "feat: add feature"

ALWAYS run bench migrate after modifying DocType JSON files. ALWAYS run bench build after modifying JS/CSS files.

3. Getting Apps from Git

bash
# Public repo
bench get-app https://github.com/org/my_app

# Specific branch
bench get-app https://github.com/org/my_app --branch develop

# Private repo via SSH
bench get-app git@github.com:org/private_app.git

# Private repo via token (v15+)
bench get-app https://TOKEN@github.com/org/private_app.git

After get-app, ALWAYS install on the target site:

bash
bench --site mysite install-app my_app

get-app clones to apps/ and adds to apps.txt. install-app creates database tables and runs after_install hooks.

4. Installing and Removing Apps

Installation Order Matters

Apps are installed in order listed in apps.txt. If App B depends on App A, App A MUST be listed first.

bash
# Install
bench --site mysite install-app my_app

# Verify
bench --site mysite list-apps
# Output: frappe, erpnext, my_app

# Remove from site (keeps code in apps/)
bench --site mysite remove-app my_app

# Remove from bench entirely (deletes code)
bench remove-app my_app

App Dependencies (v14+)

Declare in hooks.py:

python
required_apps = ["frappe", "erpnext"]

Frappe ALWAYS checks required_apps during installation and blocks if dependencies are missing.

5. Debugging with bench console

bash
bench --site mysite console

Opens an IPython REPL with Frappe context:

python
# Query data
frappe.db.sql("SELECT name, status FROM `tabSales Invoice` LIMIT 5", as_dict=True)

# Get a document
doc = frappe.get_doc("Sales Invoice", "SINV-00001")
print(doc.grand_total)

# Test a whitelisted method
from my_app.api import my_function
result = my_function(param="value")

# Check configuration
frappe.get_site_config()

# Auto-reload on code changes (v15+)
# Start with: bench --site mysite console --autoreload

ALWAYS use bench console for debugging — NEVER modify production data with raw SQL.

6. Development Mode vs Production Mode

Development Mode

bash
# Enable
bench set-config -g developer_mode 1

# Start dev server (Procfile: web + worker + redis + socketio)
bench start

Development mode enables:

  • DocType editing in Desk
  • "Is Standard" option for reports/scripts
  • Auto-reload on Python file changes
  • Detailed error tracebacks in browser
  • dev-requirements.txt dependencies installed

Production Mode

bash
# Disable developer mode
bench set-config -g developer_mode 0

# Setup production (nginx + supervisor)
sudo bench setup production USERNAME

# Restart
sudo supervisorctl restart all
# or
sudo systemctl restart supervisor

Production mode:

  • Serves via nginx (port 80/443)
  • Background workers via supervisor
  • Static files served directly by nginx
  • Errors logged to files, not browser
  • NEVER enable developer_mode on production sites

7. Asset Building

v15+ (esbuild)

bash
# Build all apps
bench build

# Build specific app
bench build --app my_custom_app

# Watch mode (auto-rebuild on changes)
bench watch

v14 (build.json)

v14 uses build.json in the app root to map source files to bundles:

json
{
    "css/my_app.css": [
        "public/css/style.css"
    ],
    "js/my_app.js": [
        "public/js/main.js"
    ]
}

Asset Include in hooks.py

python
# Desk (backend UI)
app_include_js = "my_app.bundle.js"      # v15+ bundle syntax
app_include_css = "my_app.bundle.css"

# Portal (website)
web_include_js = "my_app_web.bundle.js"
web_include_css = "my_app_web.bundle.css"

# v14 legacy syntax
app_include_js = "/assets/my_app/js/my_app.js"
app_include_css = "/assets/my_app/css/my_app.css"

ALWAYS run bench build after changing JS/CSS files. ALWAYS run bench clear-cache if assets are not updating.

8. App Versioning

Version String in init.py

python
# my_custom_app/__init__.py
__version__ = "1.2.0"

ALWAYS use semantic versioning: MAJOR.MINOR.PATCH

  • MAJOR: Breaking changes
  • MINOR: New features (backward compatible)
  • PATCH: Bug fixes

The version is read by bench version, displayed in Desk, and used by the Marketplace.

Checking Versions

bash
bench version
# frappe 15.23.0
# erpnext 15.18.0
# my_custom_app 1.2.0

9. Patches: Data Migrations

Writing a Patch

python
# my_app/patches/v1_2/update_customer_status.py
import frappe

def execute():
    frappe.reload_doc("module_name", "doctype", "customer_extension")

    frappe.db.sql("""
        UPDATE `tabCustomer Extension`
        SET status = 'Active'
        WHERE status IS NULL
    """)
    frappe.db.commit()

Registering in patches.txt

# patches.txt — v14+ supports sections

[pre_model_sync]
my_app.patches.v1_1.fix_old_data
my_app.patches.v1_2.rename_field_before_schema

[post_model_sync]
my_app.patches.v1_2.update_customer_status
my_app.patches.v1_2.migrate_settings

Section timing (v14+):

  • [pre_model_sync] — Runs BEFORE DocType schema changes are applied
  • [post_model_sync] — Runs AFTER schema changes (new fields available)
  • No section header — Runs in [pre_model_sync] by default

Patch Rules

  • ALWAYS add new patches at the END of their section
  • Patches run ONCE — tracked in tabPatch Log
  • To re-run a patch, append a comment: my_app.patches.v1_2.fix #2025-03-20
  • ALWAYS call frappe.reload_doc() before accessing new/modified DocTypes
  • ALWAYS use [post_model_sync] for patches that need new fields
  • One-liner patches: execute:frappe.delete_doc("Page", "old-page", ignore_missing=True)

Testing a Patch

bash
# Run all pending patches
bench --site mysite migrate

# Run a specific patch manually in console
bench --site mysite console
>>> from my_app.patches.v1_2.update_customer_status import execute
>>> execute()
>>> frappe.db.commit()

10. Publishing to Frappe Marketplace

Prerequisites Checklist

  1. App hosted on public GitHub repository
  2. setup.py or pyproject.toml with correct metadata
  3. Valid __version__ in __init__.py
  4. README.md with installation instructions
  5. All tests passing

setup.py (v14)

python
from setuptools import setup, find_packages

setup(
    name="my_custom_app",
    version="1.0.0",
    description="My Custom App for ERPNext",
    author="Your Name",
    author_email="you@example.com",
    packages=find_packages(),
    zip_safe=False,
    include_package_data=True,
    install_requires=["frappe"],
)

pyproject.toml (v15+)

toml
[project]
name = "my_custom_app"
dynamic = ["version"]
requires-python = ">=3.10,<3.13"
dependencies = ["frappe"]

[build-system]
requires = ["flit_core >=3.4,<4"]
build-backend = "flit_core:buildapi"

Publishing Steps

  1. Create account at https://frappecloud.com/marketplace
  2. Add your GitHub repository
  3. Configure supported versions (v14, v15)
  4. Submit for review
  5. After approval, app appears in Marketplace

11. App Update Lifecycle on Client Sites

bash
# Pull latest code
bench update --pull

# Or update specific app
cd apps/my_custom_app && git pull origin main && cd ../..

# Then migrate (runs patches + syncs schema)
bench --site mysite migrate

# Rebuild assets
bench build --app my_custom_app

# Restart workers
bench restart

The bench update command wraps: backup → pull → requirements → migrate → build → restart.

ALWAYS take a backup before running bench update on production. ALWAYS test updates on staging before applying to production.

See Also

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 Frappe Ops App Lifecycle AI skill do?

Use when scaffolding a new Frappe app, configuring app settings, building assets, running tests, deploying, updating, or publishing to marketplace. Prevents broken app structure from incorrect scaffolding, missing setup.py fields, and failed builds. Covers bench new-app, app directory structure, setup.py/pyproject.toml, hooks.py config, bench build, bench run-tests, app publishing. Keywords: app lifecycle, new-app, scaffolding, setup.py, pyproject.toml, hooks.py, bench build, app publishing, marketplace, create app, publish app, app structure, how to start new app, app directory layout..

Why use Frappe Ops App Lifecycle on TypingMind?

Because you install it once and use it with any model. Frappe Ops App Lifecycle 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 Frappe Ops App Lifecycle in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Impertio-Studio/Frappe_Claude_Skill_Package/tree/main/skills/source/ops/frappe-ops-app-lifecycle. 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 Frappe Ops App Lifecycle?

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 Frappe Ops App Lifecycle?

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

Is the Frappe Ops App Lifecycle AI skill free?

Yes. It is published on GitHub by Impertio-Studio 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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