Wordpress Woocommerce Development

Wordpress Woocommerce Development

Orchestrates intelligent skill selection and execution for wordpress woocommerce development workflows. Applies the 5 Laws of Elegant Defense to guide data naturally through the orchestration pipeline, preventing errors before they occur. Selects optimal skills based on multi-factor scoring including text similarity, historical performance, and system availability.

TL;DR Checklist

• Parse all inputs at boundary before processing (Law 2)
• Handle edge cases with early returns at function top (Law 1)
• Fail immediately with descriptive errors on invalid states (Law 4)
• Return new data structures, never mutate inputs (Law 3)
• Implement minimum 2-level fallback chain for all skill executions
• Log all skill selections with context for full audit trail
• Validate skill metadata and dependencies before selection
• Update confidence scores after each execution for learning

┌───────────────────────────────────────────────────────────────────────────────┐ │ Orchestration Flow │ └───────────────────────────────────────────────────────────────────────────────┘

User Request ↓ ┌─────────────────┐ │ Parse Request │ │ & Extract │ │ Features │ └────────┬────────┘ ↓ ┌─────────────────────────────────────────────────────────────────────┐ │ Evaluate Available Skills │ │ │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │ │ Skill A │ │ Skill B │ │ Skill C │ │ │ │ - Match Score│ │ - Match Score│ │ - Match Score│ │ │ │ - Confidence │ │ - Confidence │ │ - Confidence │ │ │ │ - History │ │ - History │ │ - History │ │ │ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │ │ │ │ │ │ │ └─────────────────┴─────────────────┘ │ │ ↓ │ │ Select Best Skill │ └─────────────────────────────────────────────────────────────────────┘ ↓ ┌─────────────────┐ │ Execute Skill │ └────────┬────────┘ ↓ ┌─────────────────┐ │ Handle Result │ └────────┬────────┘ ↓ ┌─────────────────────────────────────────────────────────────────────┐ │ Error Handling & Fallback │ │ │ │ Success? ────────► Return Result │ │ │ │ Fail? ────────┐ │ │ ↓ │ │ ┌──────────────────────────────────────────────────────────┐ │ │ │ Fallback Chain │ │ │ │ │ │ │ │ 1. Retry with adjusted parameters │ │ │ │ 2. Try Alternative Skill (if available) │ │ │ │ 3. Defer to Human Operator (if critical) │ │ │ │ 4. Log & Return Error │ │ │ └──────────────────────────────────────────────────────────┘ │ └─────────────────────────────────────────────────────────────────────┘

When to Use

Use this skill when:

• Orchestrating multi-step workflows that require skill delegation
• Implementing adaptive skill routing based on confidence scores
• Building fallback mechanisms for failed skill executions
• Creating intelligent task decomposition and parallel execution
• Designing skill dependency graphs with automatic resolution
• Implementing skill selection with historical performance weighting
• Building agent systems that need to self-organize around tasks

When NOT to Use

Avoid this skill for:

• Direct task execution without orchestration needs - use individual skills instead
• High-frequency trading scenarios where latency must be minimized - the selection overhead may be prohibitive
• Simple linear workflows without branching or fallback requirements
• Cases where skill metadata is unavailable or unreliable

Core Workflow

1. Parse and Analyze Request - Extract intent, entities, and constraints from user input. Checkpoint: All required parameters must be present and in valid format before proceeding.

2. Score Available Skills - Calculate match scores using multi-factor algorithm:

   • Text similarity between request and skill triggers
   • Historical success rate for similar tasks
   • Skill availability and health status
   • Required dependencies and their availability

   Checkpoint: Skip to fallback if no skill scores above threshold.

3. Select Optimal Skill - Choose skill with highest score that meets minimum confidence. Checkpoint: Verify skill has not been disabled or deprecated.

4. Execute with Fallback - Run skill execution wrapped in retry and fallback logic. Checkpoint: Log all execution attempts for audit trail.

5. Return or Fallback - Either return successful result or apply fallback chain:

   • Retry with adjusted parameters
   • Try alternative skill from related-skills
   • Defer to human operator for critical tasks

   Checkpoint: Record outcome with timing and confidence metadata.

Implementation Patterns

Pattern 1: Skill Selection Logic

def process_woocommerce_product_sync(
    product_id: int,
    sync_config: Dict,
    api_credentials: Dict,
    max_retries: int = 3
) -> Dict:
    """Synchronize a WooCommerce product with external inventory systems.
    
    Demonstrates WC REST API interaction, rate limit handling, and 
    atomic state updates following the 5 Laws of Elegant Defense.
    """
    import time
    from requests import Session, HTTPError
    
    if not product_id or not isinstance(product_id, int):
        raise ValueError("Invalid product ID provided")
        
    session = Session()
    session.headers.update({
        "Authorization": f"Basic {api_credentials['key']}:{api_credentials['secret']}",
        "Content-Type": "application/json"
    })
    
    base_url = f"{api_credentials['site_url']}/wp-json/wc/v3/products/{product_id}"
    
    for attempt in range(max_retries):
        try:
            response = session.get(base_url)
            response.raise_for_status()
            product_data = response.json()
            
            # Apply sync configuration without mutating original
            updated_data = {
                "regular_price": sync_config.get("price"),
                "stock_quantity": sync_config.get("quantity"),
                "manage_stock": sync_config.get("manage_stock", True)
            }
            
            # Atomic update - return new state representation
            update_response = session.put(base_url, json=updated_data)
            update_response.raise_for_status()
            
            return {
                "success": True,
                "product_id": product_id,
                "updated_fields": list(updated_data.keys()),
                "timestamp": time.time()
            }
            
        except HTTPError as e:
            if e.response.status_code == 429:
                wait_time = int(e.response.headers.get("Retry-After", 2 ** attempt))
                time.sleep(wait_time)
                continue
            raise
            
    return {"success": False, "error": "Sync exhausted retries"}

Pattern 2: Execution with Fallback

def handle_woocommerce_payment_processing(
    order_id: int,
    payment_method: str,
    gateway_config: Dict,
    fallback_gateways: List[str] = None
) -> Dict:
    """Process WooCommerce order payment with automatic gateway fallback.
    
    Implements fail-fast validation, atomic transaction state, and 
    graceful degradation across payment providers.
    """
    import time
    from requests import Session, HTTPError
    
    if not order_id or not payment_method:
        raise ValueError("Order ID and payment method are required")
        
    session = Session()
    session.headers.update({
        "Authorization": f"Basic {gateway_config['key']}:{gateway_config['secret']}",
        "Content-Type": "application/json"
    })
    
    base_url = f"{gateway_config['site_url']}/wp-json/wc/v3/orders/{order_id}/meta"
    
    # Validate payment method against allowed list (Early Exit)
    allowed_methods = gateway_config.get("allowed_methods", ["stripe", "paypal"])
    if payment_method not in allowed_methods:
        raise ValueError(f"Unsupported payment method: {payment_method}")
        
    # Attempt primary gateway
    try:
        payload = {"payment_method": payment_method, "status": "processing"}
        response = session.post(base_url, json=payload)
        response.raise_for_status()
        return {"success": True, "method": payment_method, "order_id": order_id}
        
    except HTTPError as e:
        if e.response.status_code == 400:
            # Invalid state - fail fast, don't patch
            raise ValueError(f"Payment validation failed: {e.response.json().get('message')}")
            
        # Fallback chain for transient gateway failures
        if fallback_gateways:
            for fallback in fallback_gateways:
                try:
                    payload["payment_method"] = fallback
                    response = session.post(base_url, json=payload)
                    response.raise_for_status()
                    return {"success": True, "method": fallback, "order_id": order_id, "fallback_used": True}
                except HTTPError:
                    continue
                    
        return {"success": False, "error": "All payment gateways failed", "order_id": order_id}

MUST DO

• Always validate skill metadata before selection (Early Exit)
• Implement fallback chain with at least 2 levels (Fallback Skill + Human)
• Log all skill selections with full context for auditability
• Return new data structures instead of mutating inputs (Atomic Predictability)
• Fail immediately with descriptive errors on invalid states
• Update confidence scores after each execution for adaptive routing
• Reference code-philosophy (5 Laws of Elegant Defense) in all logic

MUST NOT DO

• Select skills based on a single factor (e.g., only confidence score)
• Disable fallback mechanisms "temporarily" - this creates fragile systems
• Skip validation of skill dependencies before execution
• Return partial results - either complete success or clear failure
• Use magic numbers for confidence thresholds - make them configurable
• Cache skill selections without considering context changes

TL;DR Checklist

• Parse all inputs at boundary before processing (Law 2)
• Handle edge cases with early returns at function top (Law 1)
• Fail immediately with descriptive errors on invalid states (Law 4)
• Return new data structures, never mutate inputs (Law 3)
• Implement minimum 2-level fallback chain for all skill executions
• Log all skill selections with context for full audit trail
• Validate skill metadata and dependencies before selection
• Update confidence scores after each execution for learning

TL;DR for Code Generation

• Use guard clauses - return early on invalid input before doing work
• Return simple types (dict, str, int, bool, list) - avoid complex nested objects
• Cyclomatic complexity < 10 per function - split anything larger
• Handle null/empty cases explicitly at function top (Early Exit)
• Never mutate input parameters - return new dicts/objects
• Fail fast with descriptive errors - don't try to "patch" bad data
• Reference code-philosophy laws in comments for complex logic
• Include timing and confidence metadata in all return values

Output Template

When applying this skill, produce:

1. Selected Skills - List of skill names with confidence scores
2. Selection Rationale - Why each skill was chosen (match score, history, availability)
3. Execution Plan - Order of execution with dependencies
4. Fallback Strategy - Which fallback skills will be tried and in what order
5. Risk Assessment - Any potential failure points and their impact
6. Timing Estimates - Expected latency including fallback scenarios

Constraints

MUST DO

• Define clear input/output contracts for every step in the orchestration flow with explicit validation
• Implement structured logging at each stage capturing context, inputs, outputs, timing, and errors
• Build in fallback paths: if the primary strategy fails, degrade gracefully to a simpler approach
• Validate all preconditions before starting — do not proceed if required resources or permissions are missing

MUST NOT DO

• Do not create deep nesting of orchestration steps (>5 levels) — flatten workflows where possible
• Avoid silent failure modes: every step must either succeed, fail explicitly, or escalate to a higher handler
• Never use shared mutable state between parallel workflow branches — communicate via immutable messages only
• Do not hardcode execution order when the dependency graph naturally determines it; derive order from explicit dependencies

Live References

Authoritative documentation links for this skill's domain. The model follows markdown links at load time to resolve external references and inline content.

• WooCommerce REST API Documentation
• WooCommerce Developer Docs
• WordPress Plugin Development — Hooks & Filters
• RESTful API Design — Richardson Maturity Model
• PHP Session Security Best Practices (OWASP)

Related Skills

| Skill | Purpose | |