fix(migration-to-aws): Fix depth pseudocode direction and README scope claims

1. Fix depth-calculation.md pseudocode (Critical Issue #1)
   - Problem: Pseudocode used depends_on[R] (wrong direction)
   - Prose said 'resources that depend on R' but code did the opposite
   - Fix: Build dependents_of reverse adjacency structure
   - Now correctly processes resources that depend on R
   - Dependent resources get higher depths (deploy later)

2. Fix README.md v1.0 vs v1.1+ scope (Critical Issue awslabs#2)
   - Problem: Claimed 'IaC generation' as v1.0 feature
   - But SKILL.md line 110 says 'v1.0 is design/estimate only'
   - App code, billing data, IaC deferred to v1.1+
   - Fix: Update plugin description to 'execution planning'
   - Update workflow steps: Discover, Clarify, Design, Estimate, Execute
   - Execute phase now correctly described as 'Plan migration timeline'

Build: All linters, manifests, security scans pass ✓

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

Author: icarthick

README.md

@@ -26,11 +26,11 @@ To maximize the benefits of plugin-assisted development while maintaining securi
 
 ## Plugins
 
-| Plugin                      | Description                                                                                                        | Status    |
-| --------------------------- | ------------------------------------------------------------------------------------------------------------------ | --------- |
-| **deploy-on-aws**           | Deploy applications to AWS with architecture recommendations, cost estimates, and IaC deployment                   | Available |
-| **amazon-location-service** | Add maps, geocoding, routing, places search, and geospatial features to applications with Amazon Location Service  | Available |
-| **migration-to-aws**        | Migrate GCP infrastructure to AWS with resource discovery, architecture mapping, cost analysis, and IaC generation | Available |
+| Plugin                      | Description                                                                                                            | Status    |
+| --------------------------- | ---------------------------------------------------------------------------------------------------------------------- | --------- |
+| **deploy-on-aws**           | Deploy applications to AWS with architecture recommendations, cost estimates, and IaC deployment                       | Available |
+| **amazon-location-service** | Add maps, geocoding, routing, places search, and geospatial features to applications with Amazon Location Service      | Available |
+| **migration-to-aws**        | Migrate GCP infrastructure to AWS with resource discovery, architecture mapping, cost analysis, and execution planning | Available |
 
 ## Installation
 
@@ -119,11 +119,11 @@ Helps you systematically migrate GCP infrastructure to AWS through resource disc
 
 ### Workflow
 
-1. **Discover** - Scan GCP infrastructure (Terraform, billing, app code) and extract resources
+1. **Discover** - Scan Terraform files for GCP resources and extract infrastructure
 2. **Clarify** - Understand compute workloads and architecture patterns
 3. **Design** - Map GCP services to AWS equivalents with rationale
 4. **Estimate** - Calculate monthly AWS costs and compare to GCP
-5. **Execute** - Generate working Infrastructure-as-Code (CDK/CloudFormation)
+5. **Execute** - Plan migration timeline and identify deployment risks
 
 ### Agent Skill Triggers
 

plugins/migration-to-aws/skills/gcp-to-aws/references/clustering/terraform/depth-calculation.md

@@ -68,20 +68,27 @@ function calculateDepth(resources) {
   // Build graph
   in_degree = {}
   depends_on = {}
+  dependents_of = {}  // Reverse adjacency: resource → resources that depend on it
   for each resource R:
     in_degree[R] = count incoming edges
     depends_on[R] = R.dependencies[]
+    dependents_of[R] = []
+
+  // Populate dependents_of (reverse edges)
+  for each resource R:
+    for each D in R.dependencies[]:
+      dependents_of[D].append(R)
 
   // Initialize depth 0
   depth = {}
   queue = [R for R in resources if in_degree[R] == 0]
   for each R in queue:
     depth[R] = 0
 
-  // Process
+  // Process queue (longest path variant)
   while queue not empty:
     R = queue.dequeue()
-    for each D in depends_on[R]:
+    for each D in dependents_of[R]:  // Iterate resources that depend on R
       depth[D] = max(depth[D], depth[R] + 1)
       in_degree[D] -= 1
       if in_degree[D] == 0: