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Intelligent Automation Workflows

Version: 1.0.0 Status: Production Last Updated: December 28, 2025 Category: Automation & Integration

Workflow Overview​

This document provides a comprehensive library of intelligent automation H.P.006-WORKFLOWS for the CODITECT platform. These H.P.006-WORKFLOWS cover process automation, API integration, webhook handling, scheduled job management, and error recovery patterns. Each workflow includes detailed phase breakdowns, inputs/outputs, and success criteria to ensure reliable automation execution.

Inputs​

InputTypeRequiredDescription
trigger_sourcestringYesSource of automation trigger (webhook, schedule, api, event)
payloadobjectYesInput data for the automation workflow
contextobjectNoAdditional context (user, environment, metadata)
retry_H.P.009-CONFIGobjectNoRetry H.P.009-CONFIGuration for failure handling
notification_targetsarrayNoList of notification endpoints

Outputs​

OutputTypeDescription
execution_idstringUnique identifier for the workflow execution
statusenumExecution status (success, failed, partial, pending)
resultsobjectWorkflow execution results
metricsobjectPerformance metrics (duration, steps completed)
errorsarrayList of errors encountered during execution
audit_logarrayComplete audit trail of execution steps

Phase 1: Trigger Processing & Validation​

Initial phase handles incoming triggers and validates input data:

  1. Trigger Reception - Receive and acknowledge incoming trigger
  2. Authentication - Validate trigger source credentials
  3. Payload Validation - Schema validation of input data
  4. Rate Limiting - Check and enforce rate limits
  5. Context Enrichment - Add metadata and environment context

Phase 2: Workflow Execution​

Core execution phase runs the automation logic:

  1. Workflow Selection - Determine appropriate workflow based on trigger type
  2. Dependency Check - Verify all required services are available
  3. Step Execution - Execute workflow steps in sequence
  4. Error Handling - Handle failures with retry/fallback logic
  5. State Management - Track execution state for recovery

Phase 3: Result Processing & Notification​

Final phase processes results and sends notifications:

  1. Result Aggregation - Compile results from all execution steps
  2. Metrics Calculation - Calculate performance metrics
  3. Notification Dispatch - Send notifications to H.P.009-CONFIGured targets
  4. Audit Logging - Record complete audit trail
  5. Cleanup - Release resources and finalize execution

Automation Workflow Library​

1. api-integration-workflow​

  • Description: Connect and synchronize data between external APIs with automatic error handling and retry logic
  • Trigger: API call or webhook
  • Complexity: moderate
  • Duration: 5-15m
  • QA Integration: validation: required, review: recommended
  • Dependencies:
    • Agents: devops-engineer, integration-specialist
    • Commands: /api-sync, /validate-integration
  • Steps:
    1. API authentication - integration-specialist - Establish secure connection
    2. Data fetch - integration-specialist - Retrieve data from source API
    3. Data transformation - devops-engineer - Transform to target format
    4. Data push - integration-specialist - Send to destination API
    5. Validation - devops-engineer - Verify synchronization success
  • Tags: [api, integration, sync, automation]

2. webhook-handler-workflow​

  • Description: Process incoming webH.P.005-HOOKS with validation, routing, and response handling
  • Trigger: Incoming webhook
  • Complexity: simple
  • Duration: 1-5m
  • QA Integration: validation: required, review: optional
  • Dependencies:
    • Agents: devops-engineer
    • Commands: /webhook-process
  • Steps:
    1. Signature validation - devops-engineer - Verify webhook signature
    2. Payload parsing - devops-engineer - Parse and validate payload
    3. Event routing - devops-engineer - Route to appropriate handler
    4. Action execution - devops-engineer - Execute business logic
    5. Response - devops-engineer - Send acknowledgment response
  • Tags: [webhook, event, automation]

3. scheduled-job-workflow​

  • Description: Execute scheduled tasks with dependency management and failure recovery
  • Trigger: Cron schedule
  • Complexity: moderate
  • Duration: 5-30m
  • QA Integration: validation: required, review: recommended
  • Dependencies:
    • Agents: devops-engineer, orchestrator
    • Commands: /job-run, /job-status
  • Steps:
    1. Schedule trigger - orchestrator - Cron triggers job execution
    2. Dependency check - devops-engineer - Verify prerequisites
    3. Job execution - devops-engineer - Run scheduled task
    4. Result processing - devops-engineer - Process and store results
    5. Notification - orchestrator - Send completion notification
  • Tags: [scheduled, cron, job, automation]

4. error-recovery-workflow​

  • Description: Automated error detection and recovery with escalation paths
  • Trigger: Error event
  • Complexity: complex
  • Duration: 5-15m
  • QA Integration: validation: required, review: required
  • Dependencies:
    • Agents: devops-engineer, security-specialist
    • Commands: /error-handle, /escalate
  • Steps:
    1. Error detection - devops-engineer - Capture and classify error
    2. Impact assessment - security-specialist - Evaluate severity
    3. Recovery attempt - devops-engineer - Execute recovery strategy
    4. Escalation - devops-engineer - Escalate if recovery fails
    5. Post-mortem - security-specialist - Document incident
  • Tags: [error, recovery, resilience, automation]

5. batch-processing-workflow​

  • Description: Process large data sets in H.P.009-CONFIGurable batches with progress tracking
  • Trigger: Manual or API
  • Complexity: complex
  • Duration: 30m+
  • QA Integration: validation: required, review: required
  • Dependencies:
    • Agents: data-engineer, devops-engineer
    • Commands: /batch-process, /batch-status
  • Steps:
    1. Data partitioning - data-engineer - Split data into batches
    2. Batch processing - data-engineer - Process each batch
    3. Progress tracking - devops-engineer - Monitor completion
    4. Error handling - data-engineer - Handle batch failures
    5. Result aggregation - data-engineer - Combine batch results
  • Tags: [batch, processing, data, automation]

Success Criteria​

CriterionTargetMeasurement
Automation Success Rate>= 99.5%Successful executions / Total executions
Average Execution Time< 5s for simple, < 30s for moderateP95 latency
Error Recovery Rate>= 95%Auto-recovered errors / Total errors
Webhook Response Time< 200msP95 response latency
Scheduled Job Reliability>= 99.9%On-time executions / Scheduled executions
API Integration Uptime>= 99.5%Successful syncs / Attempted syncs

Error Handling​

Error TypeRecovery StrategyEscalation
Authentication failureRetry with token refreshAlert after 3 failures
TimeoutExponential backoff retryAlert after 5 retries
Validation errorLog and skipNone (expected behavior)
External API errorRetry with circuit breakerAlert when circuit opens
Resource exhaustionQueue and retry laterAlert on queue overflow

Maintainer: CODITECT Core Team Standard: CODITECT-STANDARD-WORKFLOWS v1.0.0