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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 workflows for the CODITECT platform. These 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_configobjectNoRetry 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 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 webhooks 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 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