planner-executor-pattern

.gitignore

@@ -259,3 +259,9 @@ Dockerfile
 01-tutorials/03-AgentCore-identity/07-Outbound_Auth_3LO_ECS_Fargate/backend/runtime/requirements.txt
 01-tutorials/03-AgentCore-identity/07-Outbound_Auth_3LO_ECS_Fargate/backend/session_binding/requirements.txt
 01-tutorials/03-AgentCore-identity/07-Outbound_Auth_3LO_ECS_Fargate/cdk.context.json
+
+### ASH ###
+.ash/
+
+### PowerPoint ###
+01-tutorials/10-Agent-Registry/01-advanced/planner-executor-pattern/images/planner-executor-architecture.pptx

01-tutorials/10-Agent-Registry/01-advanced/planner-executor-pattern/.env.example

@@ -0,0 +1,9 @@
+# AWS Configuration
+AWS_REGION=us-west-2
+
+# Auth0 OAuth Configuration (optional — leave empty to use IAM auth)
+# See the Auth0 Setup section in the notebook for instructions.
+AUTH0_DOMAIN=
+AUTH0_CLIENT_ID=
+AUTH0_CLIENT_SECRET=
+AUTH0_AUDIENCE=https://bedrock-agentcore.us-west-2.amazonaws.com

01-tutorials/10-Agent-Registry/01-advanced/planner-executor-pattern/README.md

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+# Planner + Executor: Runtime Tool Discovery with AWS Agent Registry
+
+## Overview
+
+When building AI agents that need to discover and use tools at runtime, loading every
+available tool into the LLM context upfront is expensive, slow, and wasteful. As your
+tool catalog grows — across order management, payments, shipping, notifications, and
+more — the token cost and latency of stuffing all tool schemas into every request
+becomes a real bottleneck.
+
+This notebook demonstrates the **Planner + Executor pattern**, a two-phase approach to
+runtime tool discovery that solves this problem:
+
+1. **Planner Agent** — receives a task, searches the AWS Agent Registry to discover
+   which tools are relevant, and outputs a minimal Tool Plan. It never executes
+   business logic — it only identifies what's needed.
+
+2. **Executor Agent** — loads only the tools specified in the Plan, creates live
+   connections to MCP servers and A2A agents, and executes the task step by step.
+
+This pattern delivers three key benefits:
+
+- **Runtime discovery** — agents find the right tools dynamically from the Registry
+  instead of hardcoding them, so new tools become available without redeploying agents
+- **Token optimization** — the Executor's context contains only the tools it needs
+  (e.g., 2-3 out of 12), significantly reducing input tokens and cost compared to
+  loading everything upfront
+- **Faster execution** — smaller context means faster LLM inference and fewer
+  irrelevant tool calls
+
+In this notebook you will be using **real deployed services** — 9 MCP tools on AgentCore Gateway and
+3 A2A agents on AgentCore Runtime — to run 3 end-to-end e-commerce scenarios. You will perform runtime discovery of the required MCP servers and A2A agents for each scenario using Planner agent and then use Executor agent to execute the scenario based on the plan and tools provided by the Planner agent. You will also analyze the token and cost savings that comes with runtime tool discovery and execution.
+
+## Deploying MCP tools to Amazon AgentCore Gateway and A2A agents to Amazon AgentCore Runtime
+
+Run these notebooks first to deploy the tools and agents:
+1. `00-deploy-sample-mcp-tools.ipynb` — deploys 9 MCP tools on AgentCore Gateway
+2. `00-deploy-sample-a2a-agents.ipynb` — deploys 3 A2A agents on AgentCore Runtime
+
+Both notebooks save config files (`utils/mcp_tools_config.json`, `util/sa2a_agents_config.json`)
+that this notebook loads automatically.
+
+**These MCP servers and A2A agents will be deployed to Amazon AgentCore once above notebooks are executed**
+
+| Tool | Protocol | Purpose |
+|---|---|---|
+| `order_lookup_tool` | MCP | Look up order details and list orders by customer |
+| `order_update_tool` | MCP | Update order status or shipping address |
+| `order_cancel_tool` | MCP | Cancel an order |
+| `email_send_tool` | MCP | Send transactional emails to customers |
+| `email_template_tool` | MCP | Manage reusable email templates |
+| `sms_notify_tool` | MCP | Send SMS notifications |
+| `payment_status_tool` | MCP | Look up payment status for an order |
+| `inventory_check_tool` | MCP | Check available stock for one or more SKUs |
+| `shipping_track_tool` | MCP | Track shipments and get delivery estimates |
+| `returns_processing_tool` | MCP (remote) | Process product returns and generate return labels |
+| `loyalty_rewards_tool` | MCP (remote) | Manage loyalty points and redeem rewards |
+| `payment_refund_tool` | A2A | Issue refunds with multi-step validation |
+| `inventory_reserve_tool` | A2A | Reserve inventory with rollback support |
+| `shipping_update_tool` | A2A | Create shipments with carrier selection and status updates |
+
+## Architecture
+
+![Planner + Executor architecture](images/planner-executor-architecture.png)
+
+## Tutorial
+
+- [Planner Executor Pattern](planner-executor.ipynb)