diff --git a/workflows/Route AI tasks between OpenAI agents with confidence-based email fallback-13965/readme-13965.md b/workflows/Route AI tasks between OpenAI agents with confidence-based email fallback-13965/readme-13965.md
new file mode 100644
index 000000000..7a5d84e07
--- /dev/null
+++ b/workflows/Route AI tasks between OpenAI agents with confidence-based email fallback-13965/readme-13965.md	
@@ -0,0 +1,720 @@
+Route AI tasks between OpenAI agents with confidence-based email fallback
+
+https://n8nworkflows.xyz/workflows/route-ai-tasks-between-openai-agents-with-confidence-based-email-fallback-13965
+
+
+# Route AI tasks between OpenAI agents with confidence-based email fallback
+
+## 1. Workflow Overview
+
+This workflow receives an incoming request via a webhook, asks a supervisory AI agent to classify the request as **simple** or **complex**, checks how confident that classification is, and then either:
+
+- routes the task to the appropriate AI execution path, or
+- sends an email alert for human review if confidence is too low.
+
+Its main use case is **controlled AI task routing**: using one model to classify request complexity, then using an orchestration agent to delegate execution to one of two specialized AI tools. It also introduces a **safety fallback** by notifying an administrator when the classification is uncertain.
+
+### 1.1 Input Reception and Runtime Configuration
+The workflow starts from a webhook and stores runtime values needed later, especially the user request and the confidence threshold used to decide whether automation is safe.
+
+### 1.2 Supervisory Classification
+A supervisor agent analyzes the request and produces structured JSON containing:
+- `complexity`: `simple` or `complex`
+- `confidence`: numeric score from 0 to 1
+- `reasoning`: explanation for the decision
+
+### 1.3 Confidence Gate
+The workflow compares the supervisor’s confidence score to a configured threshold. High-confidence classifications proceed to automated execution; low-confidence ones trigger an email alert.
+
+### 1.4 AI Orchestration and Specialized Execution
+If confidence is high enough, a second AI agent acts as an orchestrator. It uses the supervisor’s classification and reasoning to decide whether to call:
+- a simple task tool for lightweight requests, or
+- a complex task tool for multi-step or deeper reasoning.
+
+### 1.5 Human Fallback Notification
+If the confidence score is below threshold, the workflow sends a plain-text email containing the request, classification, confidence, reasoning, and threshold, asking for manual review.
+
+### 1.6 Webhook Response
+When automated execution succeeds, the workflow responds to the original webhook request using a dedicated response node.
+
+---
+
+## 2. Block-by-Block Analysis
+
+## 2.1 Input Reception and Runtime Configuration
+
+**Overview:**  
+This block accepts the incoming HTTP request and prepares core values used by later nodes. It currently injects placeholder configuration values rather than extracting them from the webhook payload.
+
+**Nodes Involved:**  
+- Webhook
+- Workflow Configuration
+
+### Node: Webhook
+- **Type and technical role:** `n8n-nodes-base.webhook`  
+  Entry point for the workflow. Receives an HTTP request and starts execution.
+- **Configuration choices:**  
+  - Uses a generated path: `b62c065b-ab0a-41f5-81f8-c5207fbcd892`
+  - `responseMode` is set to **responseNode**, meaning the HTTP response is not returned immediately by the webhook node itself; instead, the workflow must later use a **Respond to Webhook** node.
+- **Key expressions or variables used:**  
+  None configured directly in this node.
+- **Input and output connections:**  
+  - No input; this is the trigger.
+  - Outputs to **Workflow Configuration**.
+- **Version-specific requirements:**  
+  Type version `2.1`.
+- **Edge cases or potential failure types:**  
+  - If no Respond to Webhook node executes, callers may experience timeout or incomplete responses.
+  - If deployed behind a proxy or with incorrect webhook URL setup, requests may not reach n8n.
+  - Authentication is not configured here, so the endpoint is effectively open unless protected externally.
+- **Sub-workflow reference:**  
+  None.
+
+### Node: Workflow Configuration
+- **Type and technical role:** `n8n-nodes-base.set`  
+  Defines reusable workflow values.
+- **Configuration choices:**  
+  - Sets `userRequest` to a placeholder string: `<__PLACEHOLDER_VALUE__User task request__>`
+  - Sets `confidenceThreshold` to `0.7`
+  - `includeOtherFields` is enabled, so any incoming webhook data is preserved alongside these assigned values.
+- **Key expressions or variables used:**  
+  No dynamic expressions in assignments; values are hardcoded placeholders.
+- **Input and output connections:**  
+  - Input from **Webhook**
+  - Output to **Supervisor Agent**
+- **Version-specific requirements:**  
+  Type version `3.4`.
+- **Edge cases or potential failure types:**  
+  - As configured, this node does **not** map the actual webhook payload into `userRequest`; unless manually changed, the supervisor will always receive the placeholder text.
+  - If downstream nodes assume real user input, results will be misleading.
+- **Sub-workflow reference:**  
+  None.
+
+---
+
+## 2.2 Supervisory Classification
+
+**Overview:**  
+This block classifies the incoming request as simple or complex. It uses an OpenAI chat model plus a structured output parser to enforce a machine-readable routing decision.
+
+**Nodes Involved:**  
+- Supervisor Agent
+- OpenAI Model - Supervisor
+- Routing Decision Parser
+
+### Node: Supervisor Agent
+- **Type and technical role:** `@n8n/n8n-nodes-langchain.agent`  
+  AI agent that analyzes the request and produces a structured classification.
+- **Configuration choices:**  
+  - Prompt source: `={{ $json.userRequest }}`
+  - Prompt type: `define`
+  - System message instructs the model to:
+    1. analyze request complexity
+    2. classify as `simple` or `complex`
+    3. assign a confidence score
+    4. provide reasoning
+  - `hasOutputParser` is enabled, so it must conform to the attached structured schema.
+- **Key expressions or variables used:**  
+  - `{{ $json.userRequest }}`
+- **Input and output connections:**  
+  - Main input from **Workflow Configuration**
+  - AI language model input from **OpenAI Model - Supervisor**
+  - AI output parser input from **Routing Decision Parser**
+  - Main output to **Check Confidence Score**
+- **Version-specific requirements:**  
+  Type version `3`.
+- **Edge cases or potential failure types:**  
+  - If the model returns invalid JSON or misses required fields, the parser may fail.
+  - Ambiguous input may lead to inconsistent confidence values.
+  - Missing OpenAI credentials will prevent execution.
+- **Sub-workflow reference:**  
+  None.
+
+### Node: OpenAI Model - Supervisor
+- **Type and technical role:** `@n8n/n8n-nodes-langchain.lmChatOpenAi`  
+  Language model backend used by the Supervisor Agent.
+- **Configuration choices:**  
+  - Model selected: `gpt-4.1-mini`
+  - No additional model options are defined.
+- **Key expressions or variables used:**  
+  None.
+- **Input and output connections:**  
+  - AI language model output to **Supervisor Agent**
+- **Version-specific requirements:**  
+  Type version `1.3`.
+- **Edge cases or potential failure types:**  
+  - Invalid or missing OpenAI credentials
+  - Model availability or rate limiting
+  - Token/context issues if input becomes large
+- **Sub-workflow reference:**  
+  None.
+
+### Node: Routing Decision Parser
+- **Type and technical role:** `@n8n/n8n-nodes-langchain.outputParserStructured`  
+  Enforces a JSON schema on the supervisor’s response.
+- **Configuration choices:**  
+  Manual schema with:
+  - `complexity`: string enum `simple` or `complex`
+  - `confidence`: number between 0 and 1
+  - `reasoning`: string
+  All three fields are required.
+- **Key expressions or variables used:**  
+  None.
+- **Input and output connections:**  
+  - AI output parser output to **Supervisor Agent**
+- **Version-specific requirements:**  
+  Type version `1.3`.
+- **Edge cases or potential failure types:**  
+  - Model outputs incompatible structure
+  - Numeric confidence outside `[0,1]`
+  - Empty or malformed JSON
+- **Sub-workflow reference:**  
+  None.
+
+---
+
+## 2.3 Confidence Gate
+
+**Overview:**  
+This block decides whether the automated route is trusted enough to proceed. It compares the supervisor’s confidence score to the configured threshold.
+
+**Nodes Involved:**  
+- Check Confidence Score
+
+### Node: Check Confidence Score
+- **Type and technical role:** `n8n-nodes-base.if`  
+  Conditional branch controlling automated execution versus fallback.
+- **Configuration choices:**  
+  - Single condition:
+    - left value: `={{ $json.confidence }}`
+    - operator: number `>=`
+    - right value: `={{ $('Workflow Configuration').first().json.confidenceThreshold }}`
+  - Strict type validation is enabled.
+- **Key expressions or variables used:**  
+  - `{{ $json.confidence }}`
+  - `{{ $('Workflow Configuration').first().json.confidenceThreshold }}`
+- **Input and output connections:**  
+  - Input from **Supervisor Agent**
+  - True output to **Execute Selected Agent**
+  - False output to **Send Fallback Alert**
+- **Version-specific requirements:**  
+  Type version `2.3`.
+- **Edge cases or potential failure types:**  
+  - If `confidence` is missing or not numeric, strict validation may cause branch errors.
+  - If the threshold is changed to a non-number, comparison may fail.
+- **Sub-workflow reference:**  
+  None.
+
+---
+
+## 2.4 AI Orchestration and Specialized Execution
+
+**Overview:**  
+This block performs the actual automated handling of the request. An orchestrator agent receives the original task plus the supervisor’s classification and can call one of two specialized tool-agents.
+
+**Nodes Involved:**  
+- Execute Selected Agent
+- OpenAI Model - Executor
+- Simple Task Agent Tool(5 MINI)
+- OpenAI Model - Simple Agent
+- Complex Task Agent Tool (5.4)
+- OpenAI Model - Complex Agent GPT 5.3
+
+### Node: Execute Selected Agent
+- **Type and technical role:** `@n8n/n8n-nodes-langchain.agent`  
+  Orchestrator agent that chooses which AI tool to call.
+- **Configuration choices:**  
+  - Text input: `={{ $('Workflow Configuration').first().json.userRequest }}`
+  - Prompt type: `define`
+  - System message instructs it to:
+    1. analyze the user request
+    2. determine which specialized agent tool to call
+    3. use Simple Task Agent Tool for simple requests
+    4. use Complex Task Agent Tool for complex requests
+    5. return the selected agent’s result
+  - The system message includes:
+    - `Task complexity classification: {{ $json.complexity }}`
+    - `Reasoning: {{ $json.reasoning }}`
+- **Key expressions or variables used:**  
+  - `{{ $('Workflow Configuration').first().json.userRequest }}`
+  - `{{ $json.complexity }}`
+  - `{{ $json.reasoning }}`
+- **Input and output connections:**  
+  - Main input from **Check Confidence Score**
+  - AI language model input from **OpenAI Model - Executor**
+  - AI tool inputs from:
+    - **Simple Task Agent Tool(5 MINI)**
+    - **Complex Task Agent Tool (5.4)**
+  - Main output to **Respond to Webhook**
+- **Version-specific requirements:**  
+  Type version `3`.
+- **Edge cases or potential failure types:**  
+  - If the model ignores the classification and calls the wrong tool, routing quality degrades.
+  - If no tool is called and the agent responds directly, behavior may differ from expected design.
+  - Missing OpenAI credentials or tool connection problems will stop execution.
+- **Sub-workflow reference:**  
+  None.
+
+### Node: OpenAI Model - Executor
+- **Type and technical role:** `@n8n/n8n-nodes-langchain.lmChatOpenAi`  
+  Model used by the orchestrator agent.
+- **Configuration choices:**  
+  - Model: `gpt-4.1-mini`
+  - No extra options set.
+- **Key expressions or variables used:**  
+  None.
+- **Input and output connections:**  
+  - AI language model output to **Execute Selected Agent**
+- **Version-specific requirements:**  
+  Type version `1.3`.
+- **Edge cases or potential failure types:**  
+  - Same OpenAI issues as above: auth, rate limits, model availability
+- **Sub-workflow reference:**  
+  None.
+
+### Node: Simple Task Agent Tool(5 MINI)
+- **Type and technical role:** `@n8n/n8n-nodes-langchain.agentTool`  
+  Specialized callable AI tool for basic requests.
+- **Configuration choices:**  
+  - Tool input text: `={{ $fromAI("task", "The task to process") }}`
+  - System message positions this tool as a simple-task specialist for:
+    - basic questions
+    - simple information
+    - single-step operations
+    - quick concise answers
+  - Tool description: straightforward tasks and simple information retrieval
+- **Key expressions or variables used:**  
+  - `{{ $fromAI("task", "The task to process") }}`
+- **Input and output connections:**  
+  - AI language model input from **OpenAI Model - Simple Agent**
+  - AI tool output to **Execute Selected Agent**
+- **Version-specific requirements:**  
+  Type version `2.2`.
+- **Edge cases or potential failure types:**  
+  - If the orchestrator passes poor task content, the answer quality drops.
+  - The tool depends on the model node being correctly attached.
+- **Sub-workflow reference:**  
+  None.
+
+### Node: OpenAI Model - Simple Agent
+- **Type and technical role:** `@n8n/n8n-nodes-langchain.lmChatOpenAi`  
+  Model powering the simple-task tool.
+- **Configuration choices:**  
+  - Model: `gpt-4.1-mini`
+- **Key expressions or variables used:**  
+  None.
+- **Input and output connections:**  
+  - AI language model output to **Simple Task Agent Tool(5 MINI)**
+- **Version-specific requirements:**  
+  Type version `1.3`.
+- **Edge cases or potential failure types:**  
+  - OpenAI auth/rate limit/model issues
+- **Sub-workflow reference:**  
+  None.
+
+### Node: Complex Task Agent Tool (5.4)
+- **Type and technical role:** `@n8n/n8n-nodes-langchain.agentTool`  
+  Specialized callable AI tool for advanced requests.
+- **Configuration choices:**  
+  - Tool input text: `={{ $fromAI("task", "The task to process") }}`
+  - System message defines it as a complex-task specialist for:
+    - multi-step reasoning
+    - in-depth analysis
+    - domain expertise
+    - creative problem-solving
+    - detailed explanations
+  - Tool description emphasizes sophisticated requests requiring analysis or expertise.
+- **Key expressions or variables used:**  
+  - `{{ $fromAI("task", "The task to process") }}`
+- **Input and output connections:**  
+  - AI language model input from **OpenAI Model - Complex Agent GPT 5.3**
+  - AI tool output to **Execute Selected Agent**
+- **Version-specific requirements:**  
+  Type version `2.2`.
+- **Edge cases or potential failure types:**  
+  - Same tool invocation risks as the simple tool
+  - Potentially larger responses, which may affect latency or token usage
+- **Sub-workflow reference:**  
+  None.
+
+### Node: OpenAI Model - Complex Agent GPT 5.3
+- **Type and technical role:** `@n8n/n8n-nodes-langchain.lmChatOpenAi`  
+  Model powering the complex-task tool.
+- **Configuration choices:**  
+  - Despite the node name, the configured model value is `gpt-4.1-mini`
+  - No advanced options are set
+- **Key expressions or variables used:**  
+  None.
+- **Input and output connections:**  
+  - AI language model output to **Complex Task Agent Tool (5.4)**
+- **Version-specific requirements:**  
+  Type version `1.3`.
+- **Edge cases or potential failure types:**  
+  - Node name and actual model selection are inconsistent, which can confuse maintainers
+  - Same OpenAI auth/rate-limit/model issues
+- **Sub-workflow reference:**  
+  None.
+
+---
+
+## 2.5 Human Fallback Notification
+
+**Overview:**  
+This branch handles uncertain classifications. Instead of executing the task automatically, it sends an email to an administrator for manual review.
+
+**Nodes Involved:**  
+- Send Fallback Alert
+
+### Node: Send Fallback Alert
+- **Type and technical role:** `n8n-nodes-base.emailSend`  
+  Sends a plain-text email alert.
+- **Configuration choices:**  
+  - Subject: `Low Confidence Alert: Task Classification Uncertain`
+  - Plain text body includes:
+    - original user request
+    - classification
+    - confidence score
+    - reasoning
+    - configured threshold
+  - `toEmail` and `fromEmail` are placeholders and must be replaced
+  - `emailFormat` is `text`
+- **Key expressions or variables used:**  
+  - `{{ $('Workflow Configuration').first().json.userRequest }}`
+  - `{{ $json.complexity }}`
+  - `{{ $json.confidence }}`
+  - `{{ $json.reasoning }}`
+  - `{{ $('Workflow Configuration').first().json.confidenceThreshold }}`
+- **Input and output connections:**  
+  - Input from the false branch of **Check Confidence Score**
+  - No output connected
+- **Version-specific requirements:**  
+  Type version `2.1`.
+- **Edge cases or potential failure types:**  
+  - Missing email credentials or SMTP misconfiguration
+  - Placeholder sender/recipient addresses will cause delivery failure
+  - This branch does **not** connect to **Respond to Webhook**, so the webhook caller may not receive a response in fallback scenarios
+- **Sub-workflow reference:**  
+  None.
+
+---
+
+## 2.6 Webhook Response
+
+**Overview:**  
+This block returns the final automated result to the original HTTP caller. It only executes on the successful high-confidence automation branch.
+
+**Nodes Involved:**  
+- Respond to Webhook
+
+### Node: Respond to Webhook
+- **Type and technical role:** `n8n-nodes-base.respondToWebhook`  
+  Sends the HTTP response for workflows using webhook `responseMode: responseNode`.
+- **Configuration choices:**  
+  - No custom response options configured.
+  - It will return the incoming item data from **Execute Selected Agent** by default.
+- **Key expressions or variables used:**  
+  None explicitly configured.
+- **Input and output connections:**  
+  - Input from **Execute Selected Agent**
+- **Version-specific requirements:**  
+  Type version `1.5`.
+- **Edge cases or potential failure types:**  
+  - If upstream data is overly large or malformed, HTTP response payload may be undesirable
+  - Since no fallback branch connects here, low-confidence executions may leave the request unanswered
+- **Sub-workflow reference:**  
+  None.
+
+---
+
+## 2.7 Sticky Notes and In-Canvas Documentation
+
+**Overview:**  
+These nodes are non-executable documentation elements placed on the canvas. They explain the intent of major parts of the workflow.
+
+**Nodes Involved:**  
+- Sticky Note
+- Sticky Note1
+- Sticky Note2
+- Sticky Note3
+- Sticky Note4
+- Sticky Note5
+- Sticky Note6
+
+### Node: Sticky Note
+- **Type and technical role:** `n8n-nodes-base.stickyNote`  
+  Visual annotation for task classification area.
+- **Configuration choices:**  
+  Content explains that the Supervisor Agent analyzes the request and determines if it is simple or complex.
+- **Input and output connections:**  
+  None.
+- **Version-specific requirements:**  
+  Type version `1`.
+- **Edge cases or potential failure types:**  
+  None.
+- **Sub-workflow reference:**  
+  None.
+
+### Node: Sticky Note1
+- Same node type and purpose as above.  
+  Documents the low-confidence alert behavior.
+
+### Node: Sticky Note2
+- Same node type and purpose as above.  
+  Documents orchestration behavior between the supervisor result and the specialized tools.
+
+### Node: Sticky Note3
+- Same node type and purpose as above.  
+  Documents the distinction between simple and complex agents.
+
+### Node: Sticky Note4
+- Same node type and purpose as above.  
+  States that the workflow starts from a webhook trigger.
+
+### Node: Sticky Note5
+- Same node type and purpose as above.  
+  Labels the confidence-check area.
+
+### Node: Sticky Note6
+- Same node type and purpose as above.  
+  Provides a broad description of the workflow’s routing logic and human fallback.
+
+---
+
+## 3. Summary Table
+
+| Node Name | Node Type | Functional Role | Input Node(s) | Output Node(s) | Sticky Note |
+|---|---|---|---|---|---|
+| Webhook | n8n-nodes-base.webhook | HTTP trigger entry point |  | Workflow Configuration | ## Workflow Start  A WEBHOOK trigger starts the execution  |
+| Workflow Configuration | n8n-nodes-base.set | Stores request and threshold values | Webhook | Supervisor Agent | ## AI Task Routing with Supervisor Agent  This workflow intelligently analyzes incoming user requests and routes them to the most appropriate AI agent based on task complexity. When a request is received through the webhook, it is first stored in the configuration step along with a confidence threshold.  A Supervisor Agent then evaluates the request and classifies it as either simple or complex, returning a confidence score and reasoning for its decision. The workflow checks whether this confidence score meets the defined threshold.  If the confidence is sufficient, an orchestrator agent delegates the task to a specialized AI tool. Simple requests are handled by a Simple Task Agent, while more advanced requests are processed by a Complex Task Agent capable of deeper reasoning.  If the confidence score is too low, the workflow sends an email alert for human review, ensuring reliable and controlled AI automation. |
+| Supervisor Agent | @n8n/n8n-nodes-langchain.agent | Classifies task complexity with confidence and reasoning | Workflow Configuration; OpenAI Model - Supervisor; Routing Decision Parser | Check Confidence Score | ## Task Classification  The Supervisor Agent analyzes the user request and determines whether the task is simple or complex. |
+| Routing Decision Parser | @n8n/n8n-nodes-langchain.outputParserStructured | Enforces structured JSON classification output |  | Supervisor Agent | ## Task Classification  The Supervisor Agent analyzes the user request and determines whether the task is simple or complex. |
+| OpenAI Model - Supervisor | @n8n/n8n-nodes-langchain.lmChatOpenAi | LLM backend for supervisor classification |  | Supervisor Agent | ## Task Classification  The Supervisor Agent analyzes the user request and determines whether the task is simple or complex. |
+| Check Confidence Score | n8n-nodes-base.if | Routes high-confidence vs low-confidence outcomes | Supervisor Agent | Execute Selected Agent; Send Fallback Alert | ## Check Confidence Score |
+| Execute Selected Agent | @n8n/n8n-nodes-langchain.agent | Orchestrates which specialized AI tool should handle the request | Check Confidence Score; OpenAI Model - Executor; Simple Task Agent Tool(5 MINI); Complex Task Agent Tool (5.4) | Respond to Webhook | ## Agent Orchestration  An orchestrator AI agent decides which specialized tool to call based on the supervisor’s classification. The request is  either the Simple Task Agent or the Complex Task Agent |
+| OpenAI Model - Executor | @n8n/n8n-nodes-langchain.lmChatOpenAi | LLM backend for orchestration agent |  | Execute Selected Agent | ## Agent Orchestration  An orchestrator AI agent decides which specialized tool to call based on the supervisor’s classification. The request is  either the Simple Task Agent or the Complex Task Agent |
+| Send Fallback Alert | n8n-nodes-base.emailSend | Sends low-confidence human review email | Check Confidence Score |  | ##  Alert  If the confidence is below the configured threshold, an email alert is sent to an administrator requesting manual review to prevent incorrect automated responses. |
+| Sticky Note | n8n-nodes-base.stickyNote | Canvas documentation |  |  |  |
+| Sticky Note1 | n8n-nodes-base.stickyNote | Canvas documentation |  |  |  |
+| Sticky Note2 | n8n-nodes-base.stickyNote | Canvas documentation |  |  |  |
+| Sticky Note3 | n8n-nodes-base.stickyNote | Canvas documentation |  |  |  |
+| Sticky Note4 | n8n-nodes-base.stickyNote | Canvas documentation |  |  |  |
+| Respond to Webhook | n8n-nodes-base.respondToWebhook | Returns final HTTP response | Execute Selected Agent |  |  |
+| OpenAI Model - Complex Agent GPT 5.3 | @n8n/n8n-nodes-langchain.lmChatOpenAi | LLM backend for complex-task tool |  | Complex Task Agent Tool (5.4) | ## Two specialized agents handle task execution:  Simple Task Agent for straightforward questions and quick responses.  Complex Task Agent for multi-step reasoning, deeper analysis, and detailed explanations.  This separation improves response quality and efficiency. |
+| Complex Task Agent Tool (5.4) | @n8n/n8n-nodes-langchain.agentTool | Tool callable by orchestrator for complex tasks | OpenAI Model - Complex Agent GPT 5.3 | Execute Selected Agent | ## Two specialized agents handle task execution:  Simple Task Agent for straightforward questions and quick responses.  Complex Task Agent for multi-step reasoning, deeper analysis, and detailed explanations.  This separation improves response quality and efficiency. |
+| Simple Task Agent Tool(5 MINI) | @n8n/n8n-nodes-langchain.agentTool | Tool callable by orchestrator for simple tasks | OpenAI Model - Simple Agent | Execute Selected Agent | ## Two specialized agents handle task execution:  Simple Task Agent for straightforward questions and quick responses.  Complex Task Agent for multi-step reasoning, deeper analysis, and detailed explanations.  This separation improves response quality and efficiency. |
+| Sticky Note6 | n8n-nodes-base.stickyNote | Canvas documentation |  |  |  |
+| OpenAI Model - Simple Agent | @n8n/n8n-nodes-langchain.lmChatOpenAi | LLM backend for simple-task tool |  | Simple Task Agent Tool(5 MINI) | ## Two specialized agents handle task execution:  Simple Task Agent for straightforward questions and quick responses.  Complex Task Agent for multi-step reasoning, deeper analysis, and detailed explanations.  This separation improves response quality and efficiency. |
+| Sticky Note5 | n8n-nodes-base.stickyNote | Canvas documentation |  |  |  |
+
+---
+
+## 4. Reproducing the Workflow from Scratch
+
+1. **Create a new workflow** in n8n.
+
+2. **Add a Webhook node**
+   - Type: **Webhook**
+   - Set the HTTP path to any unique value, for example the generated UUID-style path used in the source workflow.
+   - Set **Response Mode** to **Using Respond to Webhook Node** / `responseNode`.
+
+3. **Add a Set node named “Workflow Configuration”**
+   - Type: **Set**
+   - Add field `userRequest` as **string**
+   - Add field `confidenceThreshold` as **number**
+   - Set `confidenceThreshold` to `0.7`
+   - In the provided workflow, `userRequest` is a placeholder value. For a real implementation, replace it with something from the webhook, such as:
+     - `{{$json.body.userRequest}}` or
+     - `{{$json.query.userRequest}}`
+     depending on how the webhook caller sends data.
+   - Enable **Include Other Input Fields**.
+
+4. **Connect Webhook → Workflow Configuration**
+
+5. **Add an AI Agent node named “Supervisor Agent”**
+   - Type: **AI Agent** (`@n8n/n8n-nodes-langchain.agent`)
+   - Set **Prompt Type** to **Define below**
+   - Set **Text** to:
+     - `={{ $json.userRequest }}`
+   - Enable structured output parsing.
+   - Set system message to instruct the model to:
+     - classify as `simple` or `complex`
+     - produce a confidence score between `0.0` and `1.0`
+     - provide reasoning
+
+6. **Add an OpenAI Chat Model node named “OpenAI Model - Supervisor”**
+   - Type: **OpenAI Chat Model**
+   - Choose model `gpt-4.1-mini`
+   - Attach valid **OpenAI credentials**
+
+7. **Connect OpenAI Model - Supervisor → Supervisor Agent** using the **AI Language Model** connection.
+
+8. **Add a Structured Output Parser node named “Routing Decision Parser”**
+   - Type: **Structured Output Parser**
+   - Use manual JSON schema:
+     - object with required fields:
+       - `complexity` as string enum `simple` / `complex`
+       - `confidence` as number 0 to 1
+       - `reasoning` as string
+
+9. **Connect Routing Decision Parser → Supervisor Agent** using the **AI Output Parser** connection.
+
+10. **Connect Workflow Configuration → Supervisor Agent** via the main connection.
+
+11. **Add an IF node named “Check Confidence Score”**
+   - Type: **IF**
+   - Configure one numeric condition:
+     - left: `={{ $json.confidence }}`
+     - operator: **greater than or equal**
+     - right: `={{ $('Workflow Configuration').first().json.confidenceThreshold }}`
+   - Keep strict type validation enabled.
+
+12. **Connect Supervisor Agent → Check Confidence Score**
+
+13. **Add an AI Agent node named “Execute Selected Agent”**
+   - Type: **AI Agent**
+   - Set **Prompt Type** to **Define below**
+   - Set **Text** to:
+     - `={{ $('Workflow Configuration').first().json.userRequest }}`
+   - Set system message so the agent:
+     - analyzes the request
+     - chooses the specialized tool based on supervisor classification
+     - calls simple tool for simple tasks
+     - calls complex tool for complex tasks
+     - returns the selected agent’s output
+   - Include these dynamic references in the system message:
+     - `Task complexity classification: {{ $json.complexity }}`
+     - `Reasoning: {{ $json.reasoning }}`
+
+14. **Add an OpenAI Chat Model node named “OpenAI Model - Executor”**
+   - Type: **OpenAI Chat Model**
+   - Model: `gpt-4.1-mini`
+   - Use valid OpenAI credentials
+
+15. **Connect OpenAI Model - Executor → Execute Selected Agent** via **AI Language Model**.
+
+16. **Add a Tool Agent node named “Simple Task Agent Tool(5 MINI)”**
+   - Type: **Agent Tool**
+   - Set tool input text to:
+     - `={{ $fromAI("task", "The task to process") }}`
+   - Set the system message to define it as a simple-task specialist:
+     - basic questions
+     - quick information
+     - single-step operations
+     - concise responses
+   - Add tool description similar to:
+     - “Handles straightforward tasks like basic questions and simple information retrieval”
+
+17. **Add an OpenAI Chat Model node named “OpenAI Model - Simple Agent”**
+   - Type: **OpenAI Chat Model**
+   - Model: `gpt-4.1-mini`
+   - Use valid OpenAI credentials
+
+18. **Connect OpenAI Model - Simple Agent → Simple Task Agent Tool(5 MINI)** via **AI Language Model**.
+
+19. **Connect Simple Task Agent Tool(5 MINI) → Execute Selected Agent** via **AI Tool**.
+
+20. **Add a Tool Agent node named “Complex Task Agent Tool (5.4)”**
+   - Type: **Agent Tool**
+   - Set tool input text to:
+     - `={{ $fromAI("task", "The task to process") }}`
+   - Set system message to define it as a complex-task specialist:
+     - multi-step reasoning
+     - deep analysis
+     - domain expertise
+     - creative problem-solving
+     - detailed explanations
+   - Add tool description similar to:
+     - “Handles complex tasks requiring multi-step reasoning, analysis, or domain expertise”
+
+21. **Add an OpenAI Chat Model node named “OpenAI Model - Complex Agent GPT 5.3”**
+   - Type: **OpenAI Chat Model**
+   - In the original workflow, the node name suggests a different model, but the actual configured model is `gpt-4.1-mini`
+   - You may keep the original naming for parity or rename it for clarity
+   - Use valid OpenAI credentials
+
+22. **Connect OpenAI Model - Complex Agent GPT 5.3 → Complex Task Agent Tool (5.4)** via **AI Language Model**.
+
+23. **Connect Complex Task Agent Tool (5.4) → Execute Selected Agent** via **AI Tool**.
+
+24. **Connect the true output of Check Confidence Score → Execute Selected Agent**
+
+25. **Add an Email Send node named “Send Fallback Alert”**
+   - Type: **Send Email**
+   - Configure SMTP or the email transport supported in your n8n setup
+   - Set **To Email** to the admin recipient
+   - Set **From Email** to a valid sender
+   - Set **Subject** to:
+     - `Low Confidence Alert: Task Classification Uncertain`
+   - Set email format to **text**
+   - Use a body containing:
+     - original request
+     - classification
+     - confidence score
+     - reasoning
+     - configured threshold
+   - Suggested expressions:
+     - `{{ $('Workflow Configuration').first().json.userRequest }}`
+     - `{{ $json.complexity }}`
+     - `{{ $json.confidence }}`
+     - `{{ $json.reasoning }}`
+     - `{{ $('Workflow Configuration').first().json.confidenceThreshold }}`
+
+26. **Connect the false output of Check Confidence Score → Send Fallback Alert**
+
+27. **Add a Respond to Webhook node named “Respond to Webhook”**
+   - Type: **Respond to Webhook**
+   - Default response settings are acceptable if you want to return the agent result as-is.
+
+28. **Connect Execute Selected Agent → Respond to Webhook**
+
+29. **Optionally add sticky notes** to document:
+   - workflow start
+   - task classification
+   - confidence check
+   - agent orchestration
+   - specialized agents
+   - alert behavior
+   - high-level workflow purpose
+
+30. **Configure credentials**
+   - **OpenAI credentials** for:
+     - OpenAI Model - Supervisor
+     - OpenAI Model - Executor
+     - OpenAI Model - Simple Agent
+     - OpenAI Model - Complex Agent GPT 5.3
+   - **Email/SMTP credentials** for:
+     - Send Fallback Alert
+
+31. **Test the workflow**
+   - Send a webhook request containing a real `userRequest`
+   - Confirm the supervisor returns valid structured JSON
+   - Confirm high-confidence requests reach the orchestrator and return via Respond to Webhook
+   - Confirm low-confidence requests generate email alerts
+
+32. **Recommended fixes before production**
+   - Replace the placeholder `userRequest` assignment with actual webhook input mapping
+   - Add a webhook response for the low-confidence branch as well, otherwise callers may wait indefinitely
+   - Consider adding webhook authentication
+   - Rename the complex model node if you want its label to match the actual configured model
+
+### Sub-workflow setup
+There are **no sub-workflows** and no **Execute Workflow** nodes in this workflow. All logic is implemented within a single workflow.
+
+---
+
+## 5. General Notes & Resources
+
+| Note Content | Context or Link |
+|---|---|
+| AI Task Routing with Supervisor Agent: incoming requests are analyzed, classified by complexity, then either routed to a specialized AI agent or escalated for human review if confidence is too low. | Canvas documentation |
+| Workflow Start: a webhook trigger starts the execution. | Canvas documentation |
+| Task Classification: the Supervisor Agent determines whether the task is simple or complex. | Canvas documentation |
+| Check Confidence Score | Canvas documentation |
+| Agent Orchestration: an orchestrator AI agent decides which specialized tool to call based on the supervisor’s classification. The request is either the Simple Task Agent or the Complex Task Agent. | Canvas documentation |
+| Two specialized agents handle task execution: Simple Task Agent for straightforward questions and quick responses; Complex Task Agent for multi-step reasoning, deeper analysis, and detailed explanations. This separation improves response quality and efficiency. | Canvas documentation |
+| Alert: if confidence is below the configured threshold, an email alert is sent to an administrator requesting manual review to prevent incorrect automated responses. | Canvas documentation |
+
+## Additional implementation cautions
+- The current workflow responds to the webhook only on the **high-confidence path**.
+- The current `Workflow Configuration` node uses a **placeholder request** instead of actual webhook data.
+- The node named **OpenAI Model - Complex Agent GPT 5.3** is actually configured to use **`gpt-4.1-mini`**.
\ No newline at end of file