AppFlowy Integration Skill

Prerequisites:

• AppFlowy deployed (self-hosted or cloud)
• API endpoint URL configured
• Authentication credentials (JWT token)
• Workspace ID known for operations
• Python requests library installed

Do NOT use when:

• Working with other project management tools (Jira, Asana, Trello)
• Managing local files without AppFlowy integration
• Tasks don't require project management tracking

<quick_start> AI Agents Workspace Configuration:

export APPFLOWY_API_URL="https://appflowy.ark-node.com"
export APPFLOWY_WORKSPACE_ID="c9674d81-6037-4dc3-9aa6-e2d833162b0f"
export APPFLOWY_DOCS_PARENT_ID="c7f9f933-ca10-4206-8be4-a2967f1085aa"

Credentials Location:

• Stored in: /Users/sunginkim/GIT2/ArkNode-AI/projects/appflowy-deployment/.env
• Workspace: AI Agents
• Documentation parent: c7f9f933-ca10-4206-8be4-a2967f1085aa

Access:

• Web UI: https://appflowy.ark-node.com
• WebSocket: wss://appflowy.ark-node.com/ws/v2/

Git PushSync Workflow (Recommended):

# Push to GitHub and auto-sync to AppFlowy
git add .
git commit -m "docs: update documentation"
git pushsync  # Push + sync to AppFlowy in one command

Mapping File: Create appflowy-mapping.yaml to prevent duplicate pages:

mappings:
  README.md: page-id-here
  docs/guide.md: another-page-id

Generic Project Sync (Any Repository):

# Sync with config file (uses mapping file if present)
python3 sync_project.py --config appflowy-sync.yaml

# Auto-discover and sync documentation
python3 sync_project.py --auto-discover --parent "Documentation"

# Sync specific folder
python3 sync_project.py --source docs/ --parent "API Docs"

# Preview before syncing (dry run)
python3 sync_project.py --config appflowy-sync.yaml --dry-run

# Force re-sync all files
python3 sync_project.py --config appflowy-sync.yaml --force

AI_agents Specific Sync Scripts:

# Sync AI_agents documentation to AppFlowy
cd skills/custom/appflowy-integration/scripts/
python3 sync_docs.py

# Sync AI_agents tasks to AppFlowy Kanban
python3 sync_tasks.py

# Preview before syncing (dry run)
python3 sync_docs.py --dry-run
python3 sync_tasks.py --dry-run

# Force re-sync all items
python3 sync_docs.py --force
python3 sync_tasks.py --force

Environment Variables:

export APPFLOWY_API_URL="https://appflowy.ark-node.com"
export APPFLOWY_API_TOKEN="your_jwt_token"
export APPFLOWY_WORKSPACE_ID="22bcbccd-9cf3-41ac-aa0b-28fe144ba71d"
export APPFLOWY_DOCS_PARENT_ID="parent_page_id"  # Optional: Parent page for docs
export APPFLOWY_DATABASE_ID="bb7a9c66-8088-4f71-a7b7-551f4c1adc5d"

Python Client Quick Start:

from appflowy_client import AppFlowyClient

# Initialize client (uses environment variables)
client = AppFlowyClient()

# List workspaces
workspaces = client.list_workspaces()

# List databases in workspace
databases = client.list_databases(client.workspace_id)

# Get database fields
fields = client.get_database_fields(client.workspace_id, database_id)

# Create a task
task = client.create_row(
    workspace_id=client.workspace_id,
    database_id=database_id,
    data={
        'title': 'Implement user authentication',
        'status': 'In Progress',
        'priority': 'High',
        'assignee': 'AI Agent',
        'description': 'Add JWT-based authentication'
    }
)

For detailed workflows, see:

• workflows/sync-documentation.md - Sync AI_agents docs to AppFlowy
• workflows/sync-tasks.md - Sync AI_agents tasks to Kanban board
• workflows/git-sync.md - Automated sync with git hooks and cron
• workflows/task-management.md - Creating and updating tasks
• workflows/workspace-operations.md - Workspace and database setup
• workflows/troubleshooting.md - Common issues and solutions
• references/api-reference.md - Complete API documentation </quick_start>

<success_criteria>

• AppFlowy client initialized successfully
• Can list workspaces and databases
• Can create and update tasks via API
• Authentication token valid and working
• Tasks visible in AppFlowy UI (if view exists - see limitations)
• No 401/403 authentication errors
• API responses return expected data structures </success_criteria>

<api_endpoints> Correct API Endpoints for Page Management:

AppFlowy uses a block-based Delta format for page content, NOT raw markdown. You must create pages first, then append content blocks.

1. Create Page (Empty):

POST /api/workspace/{workspace_id}/page-view
{
  "name": "Page Title",
  "layout": 0,                    // 0 = Document layout
  "parent_view_id": "parent_id"   // Optional: for nested pages
}

Response: {"data": {"view_id": "...", "database_id": null}, "code": 0}

2. Append Content Blocks:

POST /api/workspace/{workspace_id}/page-view/{page_id}/append-block
{
  "blocks": [
    {"type": "heading", "data": {"level": 1, "delta": [{"insert": "Title"}]}},
    {"type": "paragraph", "data": {"delta": [{"insert": "Text content"}]}},
    {"type": "bulleted_list", "data": {"delta": [{"insert": "List item"}]}},
    {"type": "numbered_list", "data": {"delta": [{"insert": "Numbered item"}]}},
    {"type": "code", "data": {"language": "python", "delta": [{"insert": "code"}]}},
    {"type": "quote", "data": {"delta": [{"insert": "Quote text"}]}}
  ]
}

3. Update Page Metadata (Name/Icon only):

PATCH /api/workspace/{workspace_id}/page-view/{page_id}
{
  "name": "Updated Title"
}

Note: PATCH does NOT update content. Use append-block endpoint for content.

Delta Block Format: AppFlowy uses Delta format (compatible with Quill.js):

• Each block has a type (heading, paragraph, bulleted_list, numbered_list, code, quote)
• Each block has data containing delta array with {"insert": "text"} objects
• Headings have additional level field (1-6)
• Code blocks have additional language field

Markdown to Blocks Converter: Use the markdown_to_blocks() function from update_page_content.py:

from update_page_content import markdown_to_blocks

# Convert markdown to AppFlowy blocks
blocks = markdown_to_blocks(markdown_content)

# Append to page
append_blocks_to_page(api_url, workspace_id, page_id, blocks, token)

Supported markdown elements:

• Headings (# through ######)
• Bullet lists (-, *)
• Numbered lists (1., 2., etc.)
• Code blocks (``` with language detection)
• Blockquotes (>)
• Paragraphs (regular text)
• Rich text formatting: bold, italic, code, links, strikethrough
• Tables (rendered as code blocks) </api_endpoints>

1. Documentation Sync → workflows/sync-documentation.md

   • Sync AI_agents docs to AppFlowy
   • Incremental sync with hash tracking
   • Configuration options (dry-run, force)
   • Hierarchical folder structure
   • Troubleshooting sync issues

2. Task Sync → workflows/sync-tasks.md

   • Sync AI_agents tasks to Kanban board
   • Multiple data source extraction
   • Status and priority mapping
   • Kanban column organization
   • Task deduplication logic

3. Git Sync Automation → workflows/git-sync.md

   • Git post-commit hooks
   • Cron job scheduling
   • CI/CD integration (GitHub Actions, GitLab)
   • Incremental sync strategies
   • Conflict handling (one-way sync)

4. Task Management → workflows/task-management.md

   • Create tasks
   • Update task status
   • Query and filter tasks
   • Bulk operations
   • Agent task tracking pattern
   • Daily standup summary

5. Workspace Operations → workflows/workspace-operations.md

   • Workspace setup
   • Database creation and management
   • Folder structure organization
   • View management
   • Project workspace initialization

6. Server Management → workflows/server-deployment.md

   • Start/stop AppFlowy backend
   • Monitor server health
   • Backup and restore
   • Container management
   • Auto-start configuration

7. Troubleshooting → workflows/troubleshooting.md

   • Environment variables not updating
   • WebSocket connection issues
   • View-database association problems
   • API authentication failures
   • Container restart behavior

8. API Reference → references/api-reference.md

   • Authentication endpoints
   • Workspace API
   • Database API
   • Row operations
   • Field operations
   • Error handling patterns

Method 2: Environment Variables

export APPFLOWY_API_URL="https://appflowy.ark-node.com"
export APPFLOWY_API_TOKEN="your_jwt_token_here"
export APPFLOWY_WORKSPACE_ID="your_workspace_id"

Python Client Configuration:

import os
import requests

class AppFlowyClient:
    def __init__(self):
        self.api_url = os.getenv('APPFLOWY_API_URL')
        self.token = os.getenv('APPFLOWY_API_TOKEN')
        self.workspace_id = os.getenv('APPFLOWY_WORKSPACE_ID')
        self.headers = {
            'Authorization': f'Bearer {self.token}',
            'Content-Type': 'application/json'
        }

    def _make_request(self, method, endpoint, **kwargs):
        """Make authenticated API request."""
        url = f"{self.api_url}{endpoint}"
        response = requests.request(method, url, headers=self.headers, **kwargs)
        response.raise_for_status()
        return response.json()

See references/api-reference.md for complete authentication documentation.

<error_handling> Robust Error Handling Pattern:

import logging
from requests.exceptions import RequestException, HTTPError

logger = logging.getLogger(__name__)

def safe_api_call(func):
    """Decorator for safe API calls with error handling."""
    def wrapper(*args, **kwargs):
        try:
            return func(*args, **kwargs)
        except HTTPError as e:
            if e.response.status_code == 401:
                logger.error("Authentication failed - check API token")
                raise Exception("AppFlowy authentication failed")
            elif e.response.status_code == 403:
                logger.error("Permission denied - check workspace access")
                raise Exception("Permission denied for AppFlowy resource")
            elif e.response.status_code == 404:
                logger.error(f"Resource not found: {e.request.url}")
                raise Exception("AppFlowy resource not found")
            else:
                logger.error(f"API error: {e}")
                raise
        except RequestException as e:
            logger.error(f"Network error connecting to AppFlowy: {e}")
            raise Exception("Failed to connect to AppFlowy instance")
    return wrapper

# Apply to API methods
@safe_api_call
def create_row_safe(client, workspace_id, database_id, data):
    return create_row(client, workspace_id, database_id, data)

Rate Limiting:

import time
from functools import wraps

def rate_limit(calls_per_minute=60):
    """Rate limit API calls to avoid overwhelming server."""
    min_interval = 60.0 / calls_per_minute
    last_called = [0.0]

    def decorator(func):
        @wraps(func)
        def wrapper(*args, **kwargs):
            elapsed = time.time() - last_called[0]
            left_to_wait = min_interval - elapsed
            if left_to_wait > 0:
                time.sleep(left_to_wait)
            result = func(*args, **kwargs)
            last_called[0] = time.time()
            return result
        return wrapper
    return decorator

See workflows/troubleshooting.md for specific error scenarios and solutions. </error_handling>

<best_practices> Never hardcode credentials. Use environment variables or secure credential storage.

from dotenv import load_dotenv
load_dotenv()

# Credentials loaded from .env file
api_token = os.getenv('APPFLOWY_API_TOKEN')

class AppFlowyManager:
    def __init__(self):
        self.client = AppFlowyClient()
        self._workspace_cache = None
        self._database_cache = {}

    def get_workspace_id(self):
        if not self._workspace_cache:
            workspaces = list_workspaces(self.client)
            self._workspace_cache = workspaces[0]['id']
        return self._workspace_cache

    def get_database_id(self, database_name):
        if database_name not in self._database_cache:
            databases = list_databases(self.client, self.get_workspace_id())
            db = next((d for d in databases if d['name'] == database_name), None)
            if db:
                self._database_cache[database_name] = db['id']
        return self._database_cache.get(database_name)

def validate_task_data(client, workspace_id, database_id, task_data):
    """Ensure task data matches database schema."""
    fields = get_database_fields(client, workspace_id, database_id)
    field_names = {f['name'] for f in fields}

    # Remove fields that don't exist in database
    validated = {k: v for k, v in task_data.items() if k in field_names}

    # Warn about missing fields
    missing = set(task_data.keys()) - field_names
    if missing:
        logger.warning(f"Fields not in database: {missing}")

    return validated

<security_checklist>

• Never hardcode credentials - use environment variables
• Store API tokens securely (not in git)
• Validate all user input before API calls
• Use HTTPS for production deployments
• Rotate JWT tokens regularly
• Never log API tokens or passwords
• Verify workspace/database IDs before operations
• Implement rate limiting to prevent API abuse
• Use proper error handling to avoid credential leaks
• Set up firewall rules for self-hosted instances </security_checklist>

Issue: Tasks created via REST API may not appear in the AppFlowy UI right away.

Cause: AppFlowy requires view objects (Grid, Board, Calendar) to exist as separate collab records in PostgreSQL. The REST API cannot create these view-database associations - only the UI can.

Symptoms:

• Task created successfully via API (returns row ID)
• Task exists in database (verified in PostgreSQL)
• Task does NOT appear in UI
• Browser console shows: [useViewOperations] databaseId not found for view

Solution:

1. Create a database view in AppFlowy UI first (click "+" → "Grid" or "Board")
2. Then use the API to create tasks - they will appear in the view
3. Alternative: Create tasks via browser console (uses WebSocket like UI)

Browser Console Workaround:

// This uses your existing session (no auth needed)
const WORKSPACE_ID = '22bcbccd-9cf3-41ac-aa0b-28fe144ba71d';
const DATABASE_ID = 'bb7a9c66-8088-4f71-a7b7-551f4c1adc5d';

fetch(`/api/workspace/${WORKSPACE_ID}/database/${DATABASE_ID}/row`, {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    cells: {
      phVRgL: 'Task Title',     // Description field
      YAgo8T: 'Task details',   // Text field
      SqwRg1: 'CEZD'            // Status: To Do
    }
  })
})
.then(r => r.json())
.then(d => console.log('Created:', d.data));

Reference: See workflows/troubleshooting.md for detailed diagnosis and solutions.

<anti_patterns> ❌ Don't: Continue using expired JWT tokens, causing 401 errors

✅ Do: Implement token refresh logic or re-authenticate automatically

if response.status_code == 401:
    token = refresh_jwt_token()
    retry_request()

✅ Do: List and verify resources first, use descriptive variable names

workspaces = client.list_workspaces()
arknode_workspace = next(w for w in workspaces if w['name'] == 'ArkNode Infrastructure')
workspace_id = arknode_workspace['id']

✅ Do: Create views in UI first, then use API for task operations

See workflows/troubleshooting.md for view-database association issue.

✅ Do: Use docker compose down && docker compose up -d to recreate containers

# WRONG - doesn't reload .env
docker compose restart

# RIGHT - recreates containers with new .env
docker compose down
docker compose up -d

✅ Do: Test connectivity before running operations

# Test connectivity
curl -v https://appflowy.ark-node.com/api/workspace

# Test DNS resolution
nslookup appflowy.ark-node.com

#!/usr/bin/env python3
from appflowy_client import AppFlowyClient

def track_agent_task(task_description, status="In Progress"):
    """Create or update task for agent work."""
    client = AppFlowyClient()

    task_info = {
        'title': task_description,
        'status': status,
        'assignee': 'AI Agent',
        'priority': 'Medium',
        'tags': ['automated', 'agent-work']
    }

    result = client.create_row(
        workspace_id=client.workspace_id,
        database_id=os.getenv('APPFLOWY_TODOS_DB_ID'),
        data=task_info
    )
    print(f"✅ Task tracked: {result['id']}")
    return result['id']

# Usage
task_id = track_agent_task("Implementing AppFlowy integration skill")

See workflows/task-management.md for complete patterns.

def generate_standup_summary(client, database_id):
    """Generate daily standup summary from AppFlowy tasks."""
    from datetime import datetime, timedelta

    # Get tasks updated in last 24 hours
    yesterday = (datetime.utcnow() - timedelta(days=1)).isoformat() + 'Z'
    updated_rows = client.get_updated_rows(client.workspace_id, database_id, yesterday)

    # ... organize by status and format output ...

    return formatted_summary

# Usage
standup = generate_standup_summary(client, database_id)
print(standup)

See workflows/task-management.md for complete implementation.

def generate_project_dashboard(client, database_id):
    """Create comprehensive project status dashboard."""
    # Get all tasks
    rows = client.get_database_rows(client.workspace_id, database_id)

    # Analyze status, priority, assignee workload
    # ... (see workflows/task-management.md for full code) ...

    return dashboard_output

See workflows/task-management.md for complete implementation.

Scenario 1: Using a configuration file

# appflowy-sync.yaml
parent_page: "My Project Docs"
structure:
  - folder: "Getting Started"
    documents:
      - source: "README.md"
        name: "Overview"
      - source: "docs/quickstart.md"
        name: "Quick Start"

  - folder: "API Reference"
    documents:
      - source: "docs/api/**/*.md"  # Glob pattern

  - folder: "Examples"
    documents:
      - source: "examples/*/README.md"
        name_from_path: true  # Use parent folder name

# Sync with config
python sync_project.py --config appflowy-sync.yaml

# Dry run first to preview
python sync_project.py --config appflowy-sync.yaml --dry-run

# Force re-sync all files
python sync_project.py --config appflowy-sync.yaml --force

Scenario 2: Auto-discovery mode (no config needed)

# Automatically discover and sync all documentation
python sync_project.py --auto-discover --parent "Documentation"

# Auto-discover with dry run
python sync_project.py --auto-discover --parent "Docs" --dry-run

Scenario 3: Sync specific folder

# Sync only the docs/ folder
python sync_project.py --source docs/ --parent "API Docs"

# Sync with custom project root
python sync_project.py --source docs/ --parent "Docs" --project-root /path/to/project

Scenario 4: Use with custom .env file

# For projects outside the default credential location
python sync_project.py \
  --config appflowy-sync.yaml \
  --env-file /path/to/project/.env

Integration with CI/CD:

# .github/workflows/sync-docs.yml
name: Sync Documentation to AppFlowy
on:
  push:
    branches: [main]
    paths: ['docs/**', 'README.md']

jobs:
  sync:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3

      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.9'

      - name: Install dependencies
        run: pip install requests pyyaml

      - name: Sync to AppFlowy
        env:
          APPFLOWY_API_URL: ${{ secrets.APPFLOWY_API_URL }}
          APPFLOWY_API_TOKEN: ${{ secrets.APPFLOWY_API_TOKEN }}
          APPFLOWY_WORKSPACE_ID: ${{ secrets.APPFLOWY_WORKSPACE_ID }}
        run: |
          python sync_project.py --config appflowy-sync.yaml

Benefits:

• ✅ Works with ANY project, not just AI_agents
• ✅ No code changes needed - pure configuration
• ✅ Incremental sync saves time and API calls
• ✅ Supports complex folder hierarchies
• ✅ Glob patterns for flexible file matching
• ✅ Can be integrated into git hooks, cron, or CI/CD

<related_skills> This skill works well with:

• api-endpoint-creator: When building custom integrations with AppFlowy
• database-migration: When setting up AppFlowy database schemas
• incident-response: Track incidents in AppFlowy
• deployment-workflow: Track deployment tasks in AppFlowy
• documentation-writer: Generate documentation for AppFlowy workflows </related_skills>

<integration_notes> Working with Other Tools:

Zapier Integration: AppFlowy supports Zapier, enabling no-code automation between AppFlowy and 5,000+ apps.

GitHub Integration: Combine with GitHub Actions to auto-create AppFlowy tasks from issues or PRs.

Skill Composition:

1. Use this skill for project tracking
2. Use code-related skills for implementation
3. Update AppFlowy status as work progresses </integration_notes>

<reference_guides> Documentation:

• workflows/sync-documentation.md - Sync AI_agents docs to AppFlowy
• workflows/sync-tasks.md - Sync AI_agents tasks to Kanban board
• workflows/git-sync.md - Automated sync with git hooks and cron
• workflows/task-management.md - Creating, updating, and tracking tasks
• workflows/workspace-operations.md - Workspace and database management
• workflows/server-deployment.md - Server setup and operations
• workflows/troubleshooting.md - Common issues and solutions
• references/api-reference.md - Complete API endpoint documentation
• references/setup_guide.md - Deployment and configuration guide

Sync Scripts:

• scripts/sync_project.py - Generic sync for any project (config-driven, YAML/JSON config)
• scripts/sync_docs.py - AI_agents documentation sync (hardcoded mappings)
• scripts/sync_tasks.py - AI_agents task sync from multiple data sources
• appflowy-sync.example.yaml - Example configuration for generic sync
• Support for dry-run, force sync, and custom .env files
• Hash-based change detection for efficient syncing
• One-way sync: Repository → AppFlowy (source of truth)

Generic Sync Features: The sync_project.py script is designed to work with ANY project:

• Configuration-driven: Define document structure in YAML/JSON
• Auto-discovery mode: Automatically find and sync documentation files
• Glob pattern support: Use wildcards to match multiple files (e.g., docs/**/*.md)
• Hierarchical structure: Create nested folder organization
• Incremental sync: Track changes via MD5 hashing, only sync what changed
• Flexible naming: Auto-generate page names or specify custom names
• Multiple input modes: Config file, auto-discover, or specific folder sync
• Dry-run support: Preview changes before syncing
• Force mode: Re-sync everything, ignoring cache

Other Scripts:

• scripts/appflowy_client.py - Python client library
• scripts/task_tracker.py - Task tracking utilities
• scripts/workspace_setup.py - Workspace initialization
• scripts/manage_server.sh - Server management script

External Resources:

• AppFlowy GitHub Repository
• AppFlowy Cloud Documentation
• AppFlowy API Documentation
• AppFlowy Zapier Integration </reference_guides>

<version_history> Version 2.4.0 (2025-12-08)

• NEW: Rich text formatting support (bold, italic, code, links, strikethrough)
• NEW: git pushsync workflow - Push to GitHub + auto-sync to AppFlowy
• NEW: Mapping file support (appflowy-mapping.yaml) for explicit page IDs
• NEW: Rename-and-recreate strategy for content updates (AppFlowy API limitation)
• Updated to AI Agents workspace (c9674d81-6037-4dc3-9aa6-e2d833162b0f)
• Fixed duplicate page creation issues with mapping files
• Enhanced markdown parser with inline formatting attributes
• 15 documentation pages synced successfully
• 10 tasks synced to Kanban board

Version 2.3.0 (2025-12-08)

• NEW: Generic sync script for any project (sync_project.py)
• Added YAML/JSON configuration support for flexible document mapping
• Auto-discovery mode to find documentation automatically
• Glob pattern support for matching multiple files (docs/**/*.md)
• Hierarchical folder structure with nested organization
• Multiple input modes: config file, auto-discover, or specific folder
• Created appflowy-sync.example.yaml with comprehensive examples
• Added generic sync usage examples and CI/CD integration patterns
• Updated documentation with generic sync features and benefits
• Script is now portable and can work with any repository

Version 2.2.0 (2025-12-08)

• Documented correct API endpoints (append-block for content)
• Added Delta block format documentation
• Added markdown_to_blocks converter documentation
• Updated sync_docs.py to use block-based content sync
• Documented APPFLOWY_DOCS_PARENT_ID environment variable
• Clarified two-step process: create page then append blocks
• Added supported markdown elements list
• Fixed content update workflow (PATCH only updates metadata)

Version 2.1.0 (2025-12-08)

• Added automated sync capabilities
• Created sync_docs.py for documentation syncing
• Created sync_tasks.py for task syncing
• Added workflows/sync-documentation.md
• Added workflows/sync-tasks.md
• Added workflows/git-sync.md
• Updated HTTPS URL to https://appflowy.ark-node.com
• Documented git hooks, cron jobs, and CI/CD integration
• Hash-based incremental sync with change detection
• One-way sync from repository to AppFlowy

Version 2.0.0 (2025-12-04)

• Migrated to pure XML structure
• Implemented progressive disclosure
• Split content into workflow files
• Added security checklist
• Improved YAML description with broader triggers
• Reduced main skill file from 1,256 to ~450 lines

Version 1.0.0 (2025-11-22)

• Initial creation
• Core API integration patterns
• Self-hosted deployment guides
• Task tracking workflows
• Project dashboard examples </version_history>