[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-aws-labs-gcp-to-aws":3,"mdc-9rzfps-key":37,"related-org-aws-labs-gcp-to-aws":4441,"related-repo-aws-labs-gcp-to-aws":4619},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":12,"stars":26,"repoUrl":27,"updatedAt":28,"license":29,"forks":30,"topics":31,"repo":32,"sourceUrl":35,"mdContent":36},"gcp-to-aws","migrate workloads from GCP to AWS","Migrate workloads from Google Cloud Platform to AWS — including AI and agentic workloads regardless of cloud provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, Google Cloud migration, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency\u002Fquality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},"aws-labs","AWS Labs","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Faws-labs.png","awslabs",[13,17,20,23],{"name":14,"slug":15,"type":16},"Migration","migration","tag",{"name":18,"slug":19,"type":16},"Infrastructure","infrastructure",{"name":21,"slug":22,"type":16},"AWS","aws",{"name":24,"slug":25,"type":16},"Google Cloud","google-cloud",14,"https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fstartups","2026-08-14T04:52:07.358543",null,15,[],{"repoUrl":27,"stars":26,"forks":30,"topics":33,"description":34},[],"Official AWS Startups repository that hosts plugins, skills, tools and resources to support startup builders on AWS","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fstartups\u002Ftree\u002FHEAD\u002Fadvisor\u002Fplugins\u002Faws-startup-advisor\u002Fskills\u002Fgcp-to-aws","---\nname: gcp-to-aws\ndescription: \"Migrate workloads from Google Cloud Platform to AWS — including AI and agentic workloads regardless of cloud provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, Google Cloud migration, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency\u002Fquality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.\"\n---\n\n# GCP-to-AWS Migration Skill\n\n## Philosophy\n\n- **Re-platform by default**: Select AWS services that match GCP workload types (e.g., Cloud Run → Fargate, Cloud SQL → RDS).\n- **Dev sizing unless specified**: Default to development-tier capacity (e.g., db.t4g.micro, single AZ). Upgrade only on user direction.\n- **No human one-time migration costs**: Do not present human labor, professional services, or people-time work as dollar estimates or \"one-time migration cost\" budget categories. Vendor charges grounded in data (for example GCP data transfer egress in the infra estimate when billing exists) are allowed.\n- **Multi-signal approach**: Design phase adapts based on available inputs — live gcloud discovery and\u002For Terraform IaC for infrastructure, billing data for service mapping, and app code for AI workload detection. When live and IaC both run, live is authoritative for current state and disagreements surface as drift, never silently resolved.\n- **BigQuery \u002F `google_bigquery_*`**: The skill **does not** recommend a specific AWS analytics or warehouse service. During **Clarify**, if discovery shows BigQuery (IaC `google_bigquery_*` and\u002For billing rows for BigQuery), you **must** surface the specialist advisory **before** Design (see `references\u002Fphases\u002Fclarify\u002Fclarify.md`). Design output uses **`Deferred — specialist engagement`**; keep directing the user to their **AWS account team** and\u002For a **data analytics migration partner** through Design, Estimate, and docs (see `references\u002Fphases\u002Fdesign\u002Fdesign-infra.md` BigQuery specialist gate).\n\n---\n\n## Definitions\n\n- **\"Load\"** = Read the file using the Read tool and follow its instructions. Do not summarize or skip sections.\n- **`$MIGRATION_DIR`** = The run-specific directory under `.migration\u002F` (e.g., `.migration\u002F0226-1430\u002F`). Set during Phase 1 (Discover).\n\n---\n\n## Context Loading Rules\n\nEach phase loads reference files on demand. To keep per-turn context manageable and prevent instruction-following degradation:\n\n- **Budget:** Each phase should load no more than ~800 lines of instructions (excluding user artifacts like JSON profiles and MCP tool results).\n- **Conditional loading:** Reference files with trigger conditions (e.g., `agentic_profile.is_agentic == true`) MUST NOT be loaded unless the condition is met. Do not speculatively load files.\n- **No duplication:** Model mapping tables, pricing data, and shared warnings exist in one canonical file. Other files reference them; they do not copy them inline.\n- **Progressive depth:** Phase orchestrators (`design.md`, `generate.md`) contain short routing logic that points to detailed sub-files. Load the sub-file only when its path is selected.\n\n**Conditional reference files (load ONLY when condition is true):**\n\n| File                                             | Condition                                                                                          |\n| ------------------------------------------------ | -------------------------------------------------------------------------------------------------- |\n| `design-refs\u002Fai-gemini-to-bedrock.md`            | `ai-workload-profile.json` exists AND `summary.ai_source` = `\"gemini\"` or `\"both\"`                 |\n| `design-refs\u002Fai-openai-to-bedrock.md`            | `ai-workload-profile.json` exists AND `summary.ai_source` = `\"openai\"` or `\"both\"`                 |\n| `design-refs\u002Fai-anthropic-to-bedrock.md`         | `ai-workload-profile.json` exists AND `summary.ai_source` = `\"anthropic\"`                          |\n| `design-refs\u002Fai.md`                              | `ai-workload-profile.json` exists AND `summary.ai_source` = `\"other\"`                              |\n| `design-refs\u002Fdesign-ref-harness.md`              | `agentic_profile.is_agentic == true` AND `ai_constraints.agentic.migration_approach == \"harness\"`  |\n| `design-refs\u002Fdesign-ref-agentic-to-agentcore.md` | `agentic_profile.is_agentic == true` AND `ai_constraints.agentic.migration_approach == \"strands\"`  |\n| `shared\u002Fretarget-gotchas.md`                     | `agentic_profile.is_agentic == true` AND `ai_constraints.agentic.migration_approach == \"retarget\"` |\n| `shared\u002Fgraviton.md`                             | Compute, DB, or cache in inventory OR `graviton_profile` present (Design\u002FEstimate\u002FGenerate)        |\n\nWhen adding new reference files, verify the phase's total loaded instructions remain under budget. If a new file would exceed ~800 lines when combined with other loaded refs, split it or make it conditional.\n\n**Hybrid stack budget warning:**\n\nWhen both `gcp-resource-inventory.json` AND `ai-workload-profile.json` exist, the combined design refs will approach the ~800-line budget. Output this warning to the user **before** loading the AI design refs:\n\n> \"⚠️ This is a large hybrid stack (infrastructure + AI workloads). To ensure complete and accurate recommendations, consider running the migration in two separate passes:\n>\n> **Pass 1 — Infrastructure:** Run with only your Terraform files to get infra mapping, Terraform generation, and cost estimates.\n>\n> **Pass 2 — AI workloads:** Run with only your application code to get Bedrock model recommendations, provider adapters, and AI migration artifacts.\n>\n> Continue with the combined run? (Y\u002FN)\"\n\nIf the user chooses to continue, proceed with the combined run. Load AI refs **after** infra refs to preserve infra instruction fidelity. If the user declines, stop and instruct them to re-run with a single input source type.\n\n**This warning is advisory only** — it does not block the run.\n\n---\n\n## Prerequisites\n\nUser must provide at least one GCP source:\n\n- **Live gcloud CLI** (recommended for infrastructure): an authenticated `gcloud` CLI — read-only, consent-gated live discovery of the project (see `references\u002Fphases\u002Fdiscover\u002Fdiscover-live.md`)\n- **Terraform IaC**: `.tf` files (with optional `.tfvars`, `.tfstate`)\n- **Application code**: Source files with GCP SDK or AI framework imports\n- **Billing data**: GCP billing\u002Fcost\u002Fusage export files (CSV or JSON)\n\nIf no Terraform is found (even when app code or billing files exist — they cannot produce an infrastructure inventory), offer live discovery per `discover.md` Step 1d; stop only when nothing will produce any artifact. Live discovery covers infrastructure only — AI\u002Fagentic workload detection still requires application code.\n\n---\n\n## State Machine\n\nThis is the execution controller. After completing each phase, consult this table to determine the next action.\n\n| Current State | Condition                                                                                                                  | Next Action                                                                                                                                                                                  |\n| ------------- | -------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `discover`    | `phases.discover != \"completed\"`                                                                                           | Load `references\u002Fphases\u002Fdiscover\u002Fdiscover.md`                                                                                                                                                |\n| `clarify`     | `phases.discover == \"completed\"` AND `phases.clarify != \"completed\"`                                                       | Load `references\u002Fphases\u002Fclarify\u002Fclarify.md`                                                                                                                                                  |\n| `design`      | `phases.clarify == \"completed\"` AND `phases.design != \"completed\"`                                                         | Load `references\u002Fphases\u002Fdesign\u002Fdesign.md`                                                                                                                                                    |\n| `estimate`    | `phases.design == \"completed\"` AND `phases.estimate != \"completed\"`                                                        | Load `references\u002Fphases\u002Festimate\u002Festimate.md`                                                                                                                                                |\n| `workshop`    | `current_phase == \"estimate\"` AND `phases.estimate == \"completed\"` AND `phases.workshop` is `\"pending\"` or `\"in_progress\"` | **Do not recompute Estimate.** If `workshop` is `\"pending\"`, present the post-Estimate workshop offer from `estimate.md`. If `\"in_progress\"`, load `references\u002Fphases\u002Fworkshop\u002Fworkshop.md`. |\n| `generate`    | `phases.estimate == \"completed\"` AND `phases.workshop == \"completed\"` AND `phases.generate != \"completed\"`                 | Load `references\u002Fphases\u002Fgenerate\u002Fgenerate.md` (workshop resolved — entered+exited or declined)                                                                                               |\n| `complete`    | `phases.generate == \"completed\"` AND `phases.feedback == \"pending\"`                                                        | Set `phases.feedback` to `\"completed\"` (user had two chances), then migration complete                                                                                                       |\n| `complete`    | `phases.generate == \"completed\"` AND `phases.feedback == \"completed\"`                                                      | Migration planning complete                                                                                                                                                                  |\n\n**How to determine current state (deterministic):**\n\n1. Read `$MIGRATION_DIR\u002F.phase-status.json`\n2. **Workshop resume (mandatory):** If `current_phase == \"estimate\"` AND\n   `phases.estimate == \"completed\"` AND `phases.workshop` is `\"pending\"` or\n   `\"in_progress\"`, follow the `workshop` row above — **never** re-run Estimate\n   on a plain \"continue my migration\" \u002F resume. Explicit \"what if\" \u002F \"reprice\" \u002F\n   \"workshop mode\" phrases also load `workshop.md` when Estimate artifacts exist.\n3. If `current_phase` exists (and step 2 did not apply), use it (must match one of: discover, clarify, design, estimate, generate, complete)\n4. Otherwise use ordered phase evaluation: `discover` → `clarify` → `design` → `estimate` → `generate`\n5. Pick the **first** phase in that order where `phases.\u003Cphase> != \"completed\"`; if none, state is `complete`. When evaluating `generate`, require `phases.workshop == \"completed\"` (seed `\"pending\"` on Discover so a missing key is not treated as resolved).\n\n**Phase gate checks**: If prior phase incomplete, do not advance (e.g., cannot enter estimate without completed design).\n\n**Clarify is mandatory:** Do not load `references\u002Fphases\u002Fdesign\u002Fdesign.md`, `references\u002Fphases\u002Festimate\u002Festimate.md`, or `references\u002Fphases\u002Fgenerate\u002Fgenerate.md` unless `$MIGRATION_DIR\u002F.phase-status.json` exists and `phases.clarify` is exactly `\"completed\"`. A `preferences.json` file alone is **not** sufficient proof that Clarify ran. If the user asks to skip Clarify or jump straight to Design, cost estimate, or artifact generation, refuse briefly, then load `references\u002Fphases\u002Fclarify\u002Fclarify.md` and run Phase 2. There is no exception for \"quick\" or \"obvious\" migrations.\n\n**Feedback sidebars**: Feedback is not a sequential phase — it is offered at two interleaved sidebars (after Discover and after Estimate). See the **Feedback Sidebars** section below for details.\n\n### Handoff Gate Orchestration (Fail Closed)\n\nLoad `references\u002Fshared\u002Fhandoff-gates.md` when executing any phase completion step.\n\n1. **Single `$MIGRATION_DIR`**: Use one run directory for the entire migration. Do not mix artifacts across `.migration\u002F*\u002F` sessions.\n2. **Re-read from disk**: Before each phase (and before each handoff gate), Read required artifacts from `$MIGRATION_DIR\u002F`. Do not rely on chat memory.\n3. **Advance only on `HANDOFF_OK`**: A phase is complete only when its orchestrator emits `HANDOFF_OK | phase=\u003Cname> | artifacts=...`. Do not load the next phase without it.\n4. **On `GATE_FAIL`**: Output the failure line(s) to the user in plain language. **Do NOT modify artifacts** to pass the gate. **Do NOT continue** to the next phase. Tell the user which phase to re-run.\n5. **Re-entry**: Re-running an earlier phase after downstream phases completed requires explicit user confirmation; downstream phases must be reset to `\"pending\"`. See `handoff-gates.md` re-entry table.\n\nGenerate phase additionally loads `references\u002Fshared\u002Fvalidate-artifacts.md` before writing `migration-report.html`, then `references\u002Fshared\u002Fvalidate-migration-report.md` after the HTML is written.\n\n---\n\n## State Validation\n\nWhen reading `$MIGRATION_DIR\u002F.phase-status.json`, validate before proceeding:\n\n1. **Multiple sessions**: If multiple directories exist under `.migration\u002F`, list them with their phase status and ask: [A] Resume latest, [B] Start fresh, [C] Cancel.\n2. **Invalid JSON**: If `.phase-status.json` fails to parse, STOP. Output: \"State file corrupted (invalid JSON). Delete the file and restart the current phase.\"\n3. **Unrecognized phase**: If `phases` object contains a phase not in {discover, clarify, design, estimate, workshop, generate, feedback}, STOP. Output: \"Unrecognized phase: [value]. Valid phases: discover, clarify, design, estimate, workshop, generate, feedback.\"\n4. **Unrecognized status**: If any `phases.*` value is not in {pending, in_progress, completed}, STOP. Output: \"Unrecognized status: [value]. Valid values: pending, in_progress, completed.\"\n5. **Invalid `current_phase`** (if present): If `current_phase` is not in {discover, clarify, design, estimate, generate, complete}, STOP. Output: \"Unrecognized current_phase: [value]. Valid values: discover, clarify, design, estimate, generate, complete.\" (`workshop` and `feedback` are sidebars — never `current_phase`.)\n6. **Out-of-order completion**: For ordered phases [discover, clarify, design, estimate, generate], if any later phase is `\"completed\"` while an earlier phase is not `\"completed\"`, STOP. Output: \"Inconsistent phase ordering detected. Reconcile `.phase-status.json` before resuming.\"\n7. **Multiple active phases**: Across core phases {discover, clarify, design, estimate, generate}, at most one phase may be `\"in_progress\"`. If >1, STOP. Output: \"Multiple phases are in_progress. Keep only one active phase before resuming.\" (Sidebar `workshop`\u002F`feedback` may be `in_progress` while estimate is `completed`.)\n\n---\n\n## State Management\n\nMigration state lives in `$MIGRATION_DIR` (`.migration\u002F[MMDD-HHMM]\u002F`), created by Phase 1 and persisted across invocations.\n\n**.phase-status.json schema:**\n\n```json\n{\n  \"migration_id\": \"0226-1430\",\n  \"last_updated\": \"2026-02-26T15:35:22Z\",\n  \"current_phase\": \"design\",\n  \"phases\": {\n    \"discover\": \"completed\",\n    \"clarify\": \"completed\",\n    \"design\": \"in_progress\",\n    \"estimate\": \"pending\",\n    \"workshop\": \"pending\",\n    \"generate\": \"pending\",\n    \"feedback\": \"pending\"\n  }\n}\n```\n\n**Status values:** `\"pending\"` → `\"in_progress\"` → `\"completed\"`. Never goes backward.\nFor core phases (discover, clarify, design, estimate, generate), at most one phase may be `\"in_progress\"` at any time.\n`workshop` and `feedback` are optional sidebars (never `current_phase`).\n`current_phase` is optional but recommended; when present it is authoritative.\n\nThe `.migration\u002F` directory is automatically protected by a `.gitignore` file created in Phase 1.\n\n### Phase Status Update Protocol\n\nUse **read-merge-write** updates for `.phase-status.json`:\n\n1. Read the current file before every update.\n2. Change only the phase keys being advanced and `last_updated`.\n3. Keep prior completed phases unchanged.\n4. Set `current_phase` to the next deterministic phase (or `complete` after generate).\n5. Write the full file in the same turn as your final phase work message.\n\nExample — after completing the Clarify phase, write `$MIGRATION_DIR\u002F.phase-status.json` with:\n\n```json\n{\n  \"migration_id\": \"MMDD-HHMM\",\n  \"last_updated\": \"2026-02-26T15:35:22Z\",\n  \"current_phase\": \"design\",\n  \"phases\": {\n    \"discover\": \"completed\",\n    \"clarify\": \"completed\",\n    \"design\": \"pending\",\n    \"estimate\": \"pending\",\n    \"workshop\": \"pending\",\n    \"generate\": \"pending\",\n    \"feedback\": \"pending\"\n  }\n}\n```\n\nReplace `MMDD-HHMM` with the actual migration ID, generate the `last_updated` ISO 8601 UTC timestamp yourself, and set each phase to its correct status at that point.\n\n---\n\n## Phase Summary Table\n\n| Phase        | Inputs                                                                                                                                                                   | Outputs                                                                                                                                                                                                                                       | Reference                                |\n| ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------- |\n| **Discover** | `.tf` files, app source code, and\u002For billing exports (at least one required)                                                                                             | `gcp-resource-inventory.json`, `gcp-resource-clusters.json`, `ai-workload-profile.json`, `billing-profile.json`, `.phase-status.json` updated (outputs vary by input)                                                                         | `references\u002Fphases\u002Fdiscover\u002Fdiscover.md` |\n| **Clarify**  | Discovery artifacts (`gcp-resource-inventory.json`, `gcp-resource-clusters.json`, `ai-workload-profile.json`, `billing-profile.json` — whichever exist)                  | `preferences.json`, `.phase-status.json` updated                                                                                                                                                                                              | `references\u002Fphases\u002Fclarify\u002Fclarify.md`   |\n| **Design**   | `preferences.json` + discovery artifacts                                                                                                                                 | `aws-design.json` (infra), `aws-design-ai.json` (AI), `aws-design-billing.json` (billing-only)                                                                                                                                                | `references\u002Fphases\u002Fdesign\u002Fdesign.md`     |\n| **Estimate** | `aws-design.json` or `aws-design-billing.json` or `aws-design-ai.json`, `preferences.json`                                                                               | `estimation-infra.json` or `estimation-ai.json` or `estimation-billing.json`, `.phase-status.json` updated                                                                                                                                    | `references\u002Fphases\u002Festimate\u002Festimate.md` |\n| **Workshop** | Post-Estimate infra artifacts (`gcp-resource-inventory.json`, `preferences.json`, `aws-design.json`, `estimation-infra.json`) — optional sidebar                         | `scenarios\u002F`, patched `preferences.json` \u002F design \u002F estimate; `.phase-status.json` (`workshop`)                                                                                                                                               | `references\u002Fphases\u002Fworkshop\u002Fworkshop.md` |\n| **Generate** | `estimation-infra.json` or `estimation-ai.json` or `estimation-billing.json`, `aws-design.json` or `aws-design-billing.json` or `aws-design-ai.json`, `preferences.json` | `generation-infra.json` or `generation-ai.json` or `generation-billing.json` + `terraform\u002F`, `scripts\u002F`, `ai-migration\u002F`, `validation-report.json` (when infra route active), `MIGRATION_GUIDE.md`, `README.md`, `.phase-status.json` updated | `references\u002Fphases\u002Fgenerate\u002Fgenerate.md` |\n| **Feedback** | `.phase-status.json` (discover completed minimum), all existing migration artifacts                                                                                      | `feedback.json`, `trace.json`, `.phase-status.json` updated                                                                                                                                                                                   | `references\u002Fphases\u002Ffeedback\u002Ffeedback.md` |\n\n---\n\n## MCP Servers\n\n**awspricing** (for cost estimation):\n\n- Provides `get_pricing`, `get_pricing_service_codes`, `get_pricing_service_attributes` tools\n- Only needed during Estimate phase. Discover and Design do not require it.\n- Primary pricing source: `references\u002Fshared\u002Fpricing-cache.md` (cached 2026 rates, ±5-10% for infrastructure, ±15-25% for AI models). MCP is secondary — used only for services not found in the cache.\n\n---\n\n## Files in This Skill\n\n```\ngcp-to-aws\u002F\n├── SKILL.md                                    ← You are here (orchestrator + state machine)\n│\n├── references\u002F\n│   ├── phases\u002F\n│   │   ├── discover\u002F\n│   │   │   ├── discover.md                     # Phase 1: Discover orchestrator\n│   │   │   ├── discover-iac.md                 # Terraform\u002FIaC discovery\n│   │   │   ├── discover-live.md                # Live gcloud CLI discovery (read-only, consent-gated)\n│   │   │   ├── discover-app-code.md            # App code discovery\n│   │   │   └── discover-billing.md             # Billing data discovery\n│   │   ├── clarify\u002F\n│   │   │   ├── clarify.md                     # Phase 2: Clarify orchestrator\n│   │   │   ├── clarify-global.md              # Category A: Global\u002FStrategic (Q1-Q7)\n│   │   │   ├── clarify-compute.md             # Categories B+C: Config Gaps + Compute (Q8-Q11)\n│   │   │   ├── clarify-database.md            # Category D: Database (Q12–Q13b)\n│   │   │   ├── clarify-ai.md                  # Categories F\u002FG\u002FH: AI\u002FBedrock, Agentic, Programs (Q14-Q27)\n│   │   │   └── clarify-ai-only.md             # Standalone AI-only migration flow\n│   │   ├── design\u002F\n│   │   │   ├── design.md                       # Phase 3: Design orchestrator\n│   │   │   ├── design-infra.md                 # Infrastructure design (IaC-based)\n│   │   │   ├── design-ai.md                    # AI workload design (Bedrock)\n│   │   │   └── design-billing.md               # Billing-only design (fallback)\n│   │   ├── estimate\u002F\n│   │   │   ├── estimate.md                     # Phase 4: Estimate orchestrator\n│   │   │   ├── estimate-infra.md               # Infrastructure cost analysis\n│   │   │   ├── estimate-ai.md                  # AI workload cost analysis\n│   │   │   └── estimate-billing.md             # Billing-only cost analysis\n│   │   ├── workshop\u002F\n│   │   │   ├── workshop.md                     # Sidebar: optional post-Estimate what-if\n│   │   │   ├── workshop-sheet.md               # Assumption sheet knobs\n│   │   │   ├── workshop-refresh.md             # Patch prefs → Design → Estimate → snapshot\n│   │   │   ├── workshop-compare.md             # Side-by-side scenarios\n│   │   │   └── workshop-assemble.md            # Resolve sidebar → return to Generate\n│   │   ├── generate\u002F\n│   │   │   ├── generate.md                     # Phase 5: Generate orchestrator\n│   │   │   ├── generate-infra.md               # Infrastructure migration plan\n│   │   │   ├── generate-ai.md                  # AI migration plan\n│   │   │   ├── generate-billing.md             # Billing-only migration plan\n│   │   │   ├── generate-artifacts-infra.md     # Terraform configurations\n│   │   │   ├── generate-artifacts-scripts.md  # Migration scripts\n│   │   │   ├── generate-artifacts-ai.md        # Provider adapter + test harness\n│   │   │   ├── generate-artifacts-billing.md   # Skeleton Terraform\n│   │   │   └── generate-artifacts-docs.md      # MIGRATION_GUIDE.md + README.md\n│   │   └── feedback\u002F\n│   │       ├── feedback.md                     # Phase 6: Feedback orchestrator\n│   │       └── feedback-trace.md               # Anonymized trace builder\n│   │\n│   ├── design-refs\u002F\n│   │   ├── index.md                            # Lookup table: GCP type → design-ref file\n│   │   ├── fast-path.md                        # Deterministic 1:1 mappings (Pass 1)\n│   │   ├── compute.md                          # Compute mappings (Cloud Run, GCE, GKE, etc.)\n│   │   ├── database.md                         # Database mappings (Cloud SQL, Spanner, etc.)\n│   │   ├── storage.md                          # Storage mappings (GCS, Filestore, etc.)\n│   │   ├── networking.md                       # Networking mappings (VPC, LB, DNS, etc.)\n│   │   ├── messaging.md                        # Messaging mappings (Pub\u002FSub, etc.)\n│   │   └── ai.md                               # AI mappings (Vertex AI → Bedrock)\n│   │\n│   ├── clustering\u002Fterraform\u002F\n│   │   ├── classification-rules.md             # Primary\u002Fsecondary classification\n│   │   ├── clustering-algorithm.md             # Cluster formation rules\n│   │   ├── depth-calculation.md                # Topological depth calculation\n│   │   └── typed-edges-strategy.md             # Edge type assignment\n│   │\n│   └── shared\u002F\n│       ├── schema-phase-status.md              # .phase-status.json schema (canonical reference)\n│       ├── schema-workshop-scenarios.md        # scenarios\u002F + preferences.workshop contract\n│       ├── schema-discover-iac.md              # gcp-resource-inventory + clusters schemas (loaded by discover-iac.md)\n│       ├── schema-discover-ai.md               # ai-workload-profile schema (loaded by discover-app-code.md and discover-iac.md Step 7d)\n│       ├── schema-discover-billing.md          # billing-profile schema (loaded by discover-billing.md)\n│       ├── schema-estimate-infra.md            # estimation-infra.json schema (loaded by estimate-infra.md at write time)\n│       ├── handoff-gates.md                    # Fail-closed phase handoff protocol (GATE_FAIL \u002F HANDOFF_OK)\n│       ├── validate-artifacts.md               # Pre-report validation (Generate Step 0; read-only)\n│       ├── validate-migration-report.md          # Post-write HTML completeness (Generate Step 4)\n│       ├── migration-complexity.md             # Complexity tier definitions (small\u002Fmedium\u002Flarge) for timeline scaling\n│       ├── pricing-cache.md                    # Cached AWS + source provider pricing (±5-25%, primary source)\n│       ├── graviton.md                         # Graviton\u002FARM64 tiers, mapping, per-phase rules (conditional load)\n│       ├── schema-graviton.md                  # graviton_profile + cpu_architecture + architecture_comparison schemas\n│       └── bedrock-quotas.md                   # Bedrock TPM\u002FRPM quota awareness, burndown rates, capacity planning\n```\n\n| Condition                                                     | Action                                                                                                                                                                                                                                                          |\n| ------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| No GCP sources found (no `.tf`, no app code, no billing data) | Offer live gcloud discovery per `discover.md` Step 1d. Only if declined or unavailable: Stop. Output: \"No GCP sources detected. Provide at least one source type (Terraform files, application code, or billing exports), or re-run and accept live discovery.\" |\n| `.phase-status.json` missing phase gate                       | Stop. Output: \"Cannot enter Phase X: Phase Y-1 not completed. Start from Phase Y or resume Phase Y-1.\"                                                                                                                                                          |\n| awspricing unavailable after 3 attempts                       | Display user warning about ±5-25% accuracy. Use `pricing-cache.md`. Add `pricing_source: \"cached_fallback\"` to the applicable `estimation-*.json` file.                                                                                                         |\n| User skips questions or says \"use defaults for the rest\"      | Apply documented defaults for all remaining questions (essential questions and any unconfirmed sheet rows in wizard mode; current and subsequent batches in full mode). Q2\u002FQ3 defaults add a report caveat. Phase 2 completes either way.                       |\n| `aws-design.json` missing required clusters                   | Stop Phase 4. Output: \"Re-run Phase 3 to generate missing cluster designs.\"                                                                                                                                                                                     |\n\n## Defaults\n\n- **IaC output**: Terraform configurations, migration scripts, AI migration code, and documentation\n- **Region**: `us-east-1` (unless user specifies, or GCP region → AWS region mapping suggests otherwise)\n- **Sizing**: Development tier (e.g., `db.t4g.micro` for databases, 0.5 CPU for Fargate)\n- **CPU architecture**: Graviton (ARM64) for all eligible compute when the workload is arm64-compatible; x86 only for incompatible workloads (Windows\u002F.NET Framework, GPU\u002FCUDA, RDS SQL Server). See `references\u002Fshared\u002Fgraviton.md`.\n- **Migration mode**: Adapts based on available inputs (infrastructure, AI, or billing-only)\n- **Cost currency**: USD\n- **Timeline assumption**: 2-16 weeks depending on migration complexity — small (2-6 weeks), medium (6-12 weeks), large (12-18 weeks). See `references\u002Fshared\u002Fmigration-complexity.md` for tier definitions.\n\n## Workflow Execution\n\nWhen invoked, the agent **MUST follow this exact sequence**:\n\n1. **Load phase status**: Read `.phase-status.json` from `.migration\u002F*\u002F`.\n   - If missing: Initialize for Phase 1 (Discover)\n   - If exists: Determine current phase using deterministic rules in **State Machine**\n\n2. **Determine phase to execute**:\n   - If `current_phase` exists: execute that phase.\n   - Otherwise execute the first non-completed phase in ordered list: discover → clarify → design → estimate → generate.\n   - If all ordered phases are completed: migration is complete (with feedback finalization rule).\n\n3. **Read phase reference**: Load the full reference file for the target phase.\n\n4. **Execute ALL steps in order**: Follow every numbered step in the reference file. **Do not skip, optimize, or deviate.**\n\n5. **Validate outputs**: Confirm all required output files exist with correct schema before proceeding. Phase orchestrators run **Completion Handoff Gate** checks per `shared\u002Fhandoff-gates.md`.\n\n6. **Handoff gate**: Emit `HANDOFF_OK` or `GATE_FAIL` per `shared\u002Fhandoff-gates.md`. On `GATE_FAIL`, stop — do not update phase status or load the next phase.\n\n7. **Update phase status**: Only after `HANDOFF_OK`. Use the Phase Status Update Protocol (read-merge-write) in the same turn as the phase's final output message.\n\n8. **Feedback sidebar**: After a phase completes, check if feedback is due (see rules below). This runs **before** advancing to the next phase.\n\n   - **After Discover** (if `phases.feedback` is `\"pending\"`): Output to user:\n     \"Would you like to share quick feedback (5 optional questions + anonymized usage data) to help improve this tool? Your data never includes resource names, file paths, or account IDs.\n     [A] Send feedback now\n     [B] Wait until after the Estimate phase\"\n     - If user picks **A** → Load `references\u002Fphases\u002Ffeedback\u002Ffeedback.md`, execute it, then continue to Clarify.\n     - If user picks **B** → Continue to Clarify (feedback stays `\"pending\"`).\n\n   - **After Estimate**: First offer the what-if workshop per `estimate.md`\n     (Enter workshop \u002F Proceed toward Generate) when the infra route is active.\n     Outer Estimate keeps `current_phase: estimate` until workshop is resolved.\n     Then, if `phases.feedback` is `\"pending\"`:\n     \"Would you like to share quick feedback now? (5 optional questions + anonymized usage data)\n     [A] Yes, share feedback\n     [B] No thanks, continue to Generate\"\n     - If user picks **A** → Load `references\u002Fphases\u002Ffeedback\u002Ffeedback.md`, execute it, then continue to Generate.\n     - If user picks **B** → Use the Phase Status Update Protocol to set `phases.feedback` to `\"completed\"`. Continue to Generate.\n   - **Warm start \u002F explicit what-if**: If the user says \"what if\", \"reprice\",\n     \"workshop mode\", or \"compare scenarios\" and infra Estimate artifacts exist,\n     load `references\u002Fphases\u002Fworkshop\u002Fworkshop.md` (respect Generate re-entry).\n\n   - **After Generate**: No feedback offer. 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If unable to complete a step, stop and report the exact step that failed.\n\nUser can invoke the skill again to resume from `current_phase` (or deterministic ordered evaluation when `current_phase` is absent).\n\n## Scope Notes\n\n**v1.0 includes:**\n\n- Terraform infrastructure discovery\n- Live infrastructure discovery via authenticated gcloud CLI (read-only, consent-gated, with IaC drift detection)\n- App code scanning (AI workload detection)\n- Billing data import from GCP\n- User requirement clarification (assumption-sheet wizard by default: confirm detected\u002Fassumed values, answer only essential questions; full adaptive question flow available on request)\n- Multi-path Design (infrastructure, AI workloads, billing-only fallback)\n- AWS cost estimation (from pricing API or fallback)\n- Migration artifact generation (Terraform, scripts, AI adapters, documentation)\n- Optional feedback collection with anonymized telemetry\n",{"data":38,"body":39},{"name":4,"description":6},{"type":40,"children":41},"root",[42,51,58,197,201,207,250,253,259,265,332,340,625,630,638,663,697,709,719,722,728,733,814,827,830,836,841,1234,1242,1417,1427,1501,1518,1525,1537,1660,1689,1692,1698,1710,1952,1955,1961,1981,1989,2424,2487,2507,2513,2531,2578,2590,2988,3007,3010,3016,3577,3580,3586,3596,3644,3647,3653,3663,3797,3803,3906,3912,3923,4344,4354,4373,4379,4387,4435],{"type":43,"tag":44,"props":45,"children":47},"element","h1",{"id":46},"gcp-to-aws-migration-skill",[48],{"type":49,"value":50},"text","GCP-to-AWS Migration Skill",{"type":43,"tag":52,"props":53,"children":55},"h2",{"id":54},"philosophy",[56],{"type":49,"value":57},"Philosophy",{"type":43,"tag":59,"props":60,"children":61},"ul",{},[62,74,84,94,104],{"type":43,"tag":63,"props":64,"children":65},"li",{},[66,72],{"type":43,"tag":67,"props":68,"children":69},"strong",{},[70],{"type":49,"value":71},"Re-platform by default",{"type":49,"value":73},": Select AWS services that match GCP workload types (e.g., Cloud Run → Fargate, Cloud SQL → RDS).",{"type":43,"tag":63,"props":75,"children":76},{},[77,82],{"type":43,"tag":67,"props":78,"children":79},{},[80],{"type":49,"value":81},"Dev sizing unless specified",{"type":49,"value":83},": Default to development-tier capacity (e.g., db.t4g.micro, single AZ). 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Phase 2: Clarify orchestrator\n│   │   │   ├── clarify-global.md              # Category A: Global\u002FStrategic (Q1-Q7)\n│   │   │   ├── clarify-compute.md             # Categories B+C: Config Gaps + Compute (Q8-Q11)\n│   │   │   ├── clarify-database.md            # Category D: Database (Q12–Q13b)\n│   │   │   ├── clarify-ai.md                  # Categories F\u002FG\u002FH: AI\u002FBedrock, Agentic, Programs (Q14-Q27)\n│   │   │   └── clarify-ai-only.md             # Standalone AI-only migration flow\n│   │   ├── design\u002F\n│   │   │   ├── design.md                       # Phase 3: Design orchestrator\n│   │   │   ├── design-infra.md                 # Infrastructure design (IaC-based)\n│   │   │   ├── design-ai.md                    # AI workload design (Bedrock)\n│   │   │   └── design-billing.md               # Billing-only design (fallback)\n│   │   ├── estimate\u002F\n│   │   │   ├── estimate.md                     # Phase 4: Estimate orchestrator\n│   │   │   ├── estimate-infra.md               # Infrastructure cost analysis\n│   │   │   ├── estimate-ai.md                  # AI workload cost analysis\n│   │   │   └── estimate-billing.md             # Billing-only cost analysis\n│   │   ├── workshop\u002F\n│   │   │   ├── workshop.md                     # Sidebar: optional post-Estimate what-if\n│   │   │   ├── workshop-sheet.md               # Assumption sheet knobs\n│   │   │   ├── workshop-refresh.md             # Patch prefs → Design → Estimate → snapshot\n│   │   │   ├── workshop-compare.md             # Side-by-side scenarios\n│   │   │   └── workshop-assemble.md            # Resolve sidebar → return to Generate\n│   │   ├── generate\u002F\n│   │   │   ├── generate.md                     # Phase 5: Generate orchestrator\n│   │   │   ├── generate-infra.md               # Infrastructure migration plan\n│   │   │   ├── generate-ai.md                  # AI migration plan\n│   │   │   ├── generate-billing.md             # Billing-only migration plan\n│   │   │   ├── generate-artifacts-infra.md     # Terraform configurations\n│   │   │   ├── generate-artifacts-scripts.md  # Migration scripts\n│   │   │   ├── generate-artifacts-ai.md        # Provider adapter + test harness\n│   │   │   ├── generate-artifacts-billing.md   # Skeleton Terraform\n│   │   │   └── generate-artifacts-docs.md      # MIGRATION_GUIDE.md + README.md\n│   │   └── feedback\u002F\n│   │       ├── feedback.md                     # Phase 6: Feedback orchestrator\n│   │       └── feedback-trace.md               # Anonymized trace builder\n│   │\n│   ├── design-refs\u002F\n│   │   ├── index.md                            # Lookup table: GCP type → design-ref file\n│   │   ├── fast-path.md                        # Deterministic 1:1 mappings (Pass 1)\n│   │   ├── compute.md                          # Compute mappings (Cloud Run, GCE, GKE, etc.)\n│   │   ├── database.md                         # Database mappings (Cloud SQL, Spanner, etc.)\n│   │   ├── storage.md                          # Storage mappings (GCS, Filestore, etc.)\n│   │   ├── networking.md                       # Networking mappings (VPC, LB, DNS, etc.)\n│   │   ├── messaging.md                        # Messaging mappings (Pub\u002FSub, etc.)\n│   │   └── ai.md                               # AI mappings (Vertex AI → Bedrock)\n│   │\n│   ├── clustering\u002Fterraform\u002F\n│   │   ├── classification-rules.md             # Primary\u002Fsecondary classification\n│   │   ├── clustering-algorithm.md             # Cluster formation rules\n│   │   ├── depth-calculation.md                # Topological depth calculation\n│   │   └── typed-edges-strategy.md             # Edge type assignment\n│   │\n│   └── shared\u002F\n│       ├── schema-phase-status.md              # .phase-status.json schema (canonical reference)\n│       ├── schema-workshop-scenarios.md        # scenarios\u002F + preferences.workshop contract\n│       ├── schema-discover-iac.md              # gcp-resource-inventory + clusters schemas (loaded by discover-iac.md)\n│       ├── schema-discover-ai.md               # ai-workload-profile schema (loaded by discover-app-code.md and discover-iac.md Step 7d)\n│       ├── schema-discover-billing.md          # billing-profile schema (loaded by discover-billing.md)\n│       ├── schema-estimate-infra.md            # estimation-infra.json schema (loaded by estimate-infra.md at write time)\n│       ├── handoff-gates.md                    # Fail-closed phase handoff protocol (GATE_FAIL \u002F HANDOFF_OK)\n│       ├── validate-artifacts.md               # Pre-report validation (Generate Step 0; read-only)\n│       ├── validate-migration-report.md          # Post-write HTML completeness (Generate Step 4)\n│       ├── migration-complexity.md             # Complexity tier definitions (small\u002Fmedium\u002Flarge) for timeline scaling\n│       ├── pricing-cache.md                    # Cached AWS + source provider pricing (±5-25%, primary source)\n│       ├── graviton.md                         # Graviton\u002FARM64 tiers, mapping, per-phase rules (conditional load)\n│       ├── schema-graviton.md                  # graviton_profile + cpu_architecture + architecture_comparison schemas\n│       └── bedrock-quotas.md                   # 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Use when debugging AgentCore agent sessions, tracing tool calls, or analyzing latency.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4449,4450,4453,4456],{"name":21,"slug":22,"type":16},{"name":4451,"slug":4452,"type":16},"Debugging","debugging",{"name":4454,"slug":4455,"type":16},"Logs","logs",{"name":4457,"slug":4458,"type":16},"Observability","observability",9427,"https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fmcp","2026-07-12T08:37:22.601527",{"slug":4463,"name":4464,"fn":4465,"description":4466,"org":4467,"tags":4468,"stars":4459,"repoUrl":4460,"updatedAt":4482},"amazon-aurora-dsql","amazon aurora dsql","build applications with Aurora DSQL","Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, FK replacement code generation, OCC retry patterns, ORM migration (Django\u002FHibernate\u002FRails), DDL operations, query plan explainability, SQL compatibility validation, and bulk data loading. Triggers on phrases like: DSQL, Aurora DSQL, create DSQL table, DSQL schema, migrate to DSQL, distributed SQL database, serverless PostgreSQL-compatible database, DSQL query plan, DSQL EXPLAIN ANALYZE, why is my DSQL query slow, DSQL foreign key, DSQL OCC retry, DSQL multi-region, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4469,4472,4473,4476,4479],{"name":4470,"slug":4471,"type":16},"Aurora","aurora",{"name":21,"slug":22,"type":16},{"name":4474,"slug":4475,"type":16},"Database","database",{"name":4477,"slug":4478,"type":16},"Serverless","serverless",{"name":4480,"slug":4481,"type":16},"SQL","sql","2026-08-04T05:35:10.770847",{"slug":4484,"name":4485,"fn":4465,"description":4466,"org":4486,"tags":4487,"stars":4459,"repoUrl":4460,"updatedAt":4492},"aurora-dsql","aurora dsql",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4488,4489,4490,4491],{"name":21,"slug":22,"type":16},{"name":4474,"slug":4475,"type":16},{"name":4477,"slug":4478,"type":16},{"name":4480,"slug":4481,"type":16},"2026-08-04T05:35:05.694395",{"slug":4494,"name":4495,"fn":4465,"description":4466,"org":4496,"tags":4497,"stars":4459,"repoUrl":4460,"updatedAt":4503},"aws-dsql","aws dsql",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4498,4499,4500,4501,4502],{"name":21,"slug":22,"type":16},{"name":4474,"slug":4475,"type":16},{"name":14,"slug":15,"type":16},{"name":4477,"slug":4478,"type":16},{"name":4480,"slug":4481,"type":16},"2026-08-04T05:35:08.749669",{"slug":4505,"name":4506,"fn":4465,"description":4466,"org":4507,"tags":4508,"stars":4459,"repoUrl":4460,"updatedAt":4516},"distributed-postgres","distributed postgres",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4509,4510,4511,4514,4515],{"name":21,"slug":22,"type":16},{"name":4474,"slug":4475,"type":16},{"name":4512,"slug":4513,"type":16},"PostgreSQL","postgresql",{"name":4477,"slug":4478,"type":16},{"name":4480,"slug":4481,"type":16},"2026-08-04T05:35:06.713102",{"slug":4518,"name":4519,"fn":4465,"description":4466,"org":4520,"tags":4521,"stars":4459,"repoUrl":4460,"updatedAt":4526},"distributed-sql","distributed sql",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4522,4523,4524,4525],{"name":21,"slug":22,"type":16},{"name":4474,"slug":4475,"type":16},{"name":4477,"slug":4478,"type":16},{"name":4480,"slug":4481,"type":16},"2026-08-04T05:35:10.086942",{"slug":4528,"name":4528,"fn":4465,"description":4466,"org":4529,"tags":4530,"stars":4459,"repoUrl":4460,"updatedAt":4536},"dsql",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4531,4532,4533,4534,4535],{"name":21,"slug":22,"type":16},{"name":4474,"slug":4475,"type":16},{"name":14,"slug":15,"type":16},{"name":4477,"slug":4478,"type":16},{"name":4480,"slug":4481,"type":16},"2026-08-04T05:35:07.751779",{"slug":4538,"name":4538,"fn":4539,"description":4540,"org":4541,"tags":4542,"stars":4555,"repoUrl":4556,"updatedAt":4557},"cost-efficiency-analyzer","analyze cost efficiency and expenses","Analyzes cost structure, cost efficiency, and expense management from P&L data. Use when the user asks about costs, expenses, COGS, operating expenses, cost ratios, cost control, spending efficiency, margin compression from cost side, or wants to understand where money is going. Also use for \"are we spending too much\", \"cost breakdown\", \"expense analysis\", or \"how efficient are our operations\". NOT for revenue or top-line analysis.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4543,4546,4549,4552],{"name":4544,"slug":4545,"type":16},"Accounting","accounting",{"name":4547,"slug":4548,"type":16},"Analytics","analytics",{"name":4550,"slug":4551,"type":16},"Cost Optimization","cost-optimization",{"name":4553,"slug":4554,"type":16},"Finance","finance",3176,"https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fagentcore-samples","2026-07-12T08:40:03.29555",{"slug":4559,"name":4559,"fn":4560,"description":4561,"org":4562,"tags":4563,"stars":4555,"repoUrl":4556,"updatedAt":4572},"executive-financial-briefing","generate executive financial briefings","Generates a concise executive-level financial briefing or summary suitable for a CEO, CFO, or board presentation. Use when the user asks for a summary, briefing, executive summary, board update, financial overview, financial health check, or \"how is the business doing\". Covers the full P&L picture in one page. Also use for \"give me the highlights\", \"what do I need to know\", or \"quick financial update\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4564,4565,4566,4569],{"name":21,"slug":22,"type":16},{"name":4553,"slug":4554,"type":16},{"name":4567,"slug":4568,"type":16},"Management","management",{"name":4570,"slug":4571,"type":16},"Reporting","reporting","2026-07-12T08:40:02.066471",{"slug":4574,"name":4574,"fn":4575,"description":4576,"org":4577,"tags":4578,"stars":4555,"repoUrl":4556,"updatedAt":4587},"multi-quarter-trend-analysis","analyze multi-quarter financial trends","Analyzes financial trends across multiple quarters by comparing P&L metrics over time. Use when the user wants to see trends, patterns, trajectories, or directional movement across 3 or more quarters. Also use for \"how are we trending\", \"show me the trend\", \"track performance over time\", \"quarter over quarter comparison across all quarters\", or any multi-period longitudinal analysis.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4579,4580,4581,4584],{"name":4547,"slug":4548,"type":16},{"name":4553,"slug":4554,"type":16},{"name":4582,"slug":4583,"type":16},"Financial Statements","financial-statements",{"name":4585,"slug":4586,"type":16},"Variance Analysis","variance-analysis","2026-07-12T08:40:00.79141",{"slug":4589,"name":4589,"fn":4590,"description":4591,"org":4592,"tags":4593,"stars":4555,"repoUrl":4556,"updatedAt":4602},"pdf","process and manipulate PDF documents","Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text\u002Ftables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting\u002Fdecrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4594,4597,4600],{"name":4595,"slug":4596,"type":16},"Automation","automation",{"name":4598,"slug":4599,"type":16},"Documents","documents",{"name":4601,"slug":4589,"type":16},"PDF","2026-07-12T08:41:44.135656",{"slug":4604,"name":4604,"fn":4605,"description":4606,"org":4607,"tags":4608,"stars":4555,"repoUrl":4556,"updatedAt":4617},"quarterly-kpi-calculator","calculate quarterly financial KPIs","Calculates quarterly financial KPIs from P&L data. P&L figures can be provided directly by the user or fetched from the financial data MCP server. Use when the user wants KPI calculations such as Gross Margin %, EBITDA Margin %, Operating Expense Ratio, or Revenue Growth % QoQ. Also use for quarterly performance review, P&L analysis, or interpreting financial ratios against benchmarks.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4609,4610,4613,4614],{"name":4544,"slug":4545,"type":16},{"name":4611,"slug":4612,"type":16},"Data Analysis","data-analysis",{"name":4553,"slug":4554,"type":16},{"name":4615,"slug":4616,"type":16},"KPI","kpi","2026-07-12T08:39:59.54971",125,{"items":4620,"total":2231},[4621,4638,4652,4659,4672,4689,4707],{"slug":4622,"name":4622,"fn":4623,"description":4624,"org":4625,"tags":4626,"stars":26,"repoUrl":27,"updatedAt":4637},"agent-advisor","plan and build AWS AI agents","Unified entry point for AI-agent work on AWS: evaluate and pick a runtime, generate a full migration plan (for existing workloads), and build an executable POC — all in one flow. Triggers on: which runtime for my agent, AgentCore vs ECS vs EKS vs Lambda, AgentCore vs Lambda MicroVMs, deploy an AI agent on AWS, agent architecture on AWS, I have an agent idea what do I build, move my agents to AWS, migrate my agents to AWS with a plan, agent migration plan, add AgentCore services, add memory\u002Fgateway\u002Fidentity\u002Fpolicy to my agent, enable AgentCore Memory, add observability to my agent, I'm already on AWS and want to add agent capabilities, migrate Temporal workers to AWS, Temporal to AWS, run Temporal on AWS, Temporal workers on AWS, we use Temporal and want to move to AWS, our service is orchestrated by Temporal, what do I build on AWS for my Temporal workers, move a Temporal-based service to AWS, Temporal Cloud or self-hosted on AWS. Runs a phased flow: Intake (entry point + technical background), Discover (lightweight code detection), Clarify (adaptive questions), deterministic scoring, Design (runtime + deployment model + services + model), Estimate (coarse cost), Generate (layered recommendation doc + scaffolding), then optional gated stages: Migration Plan (full plan generated in-skill by reusing this plugin's gcp-to-aws engine, with the advisor's decisions carried over) and POC (deployment plan + deployable proof-of-concept on the recommended runtime — AgentCore, ECS, EKS, or Lambda; generated deliverables by default, or assisted build in your account on explicit opt-in). Systems with several workloads (interacting or independent agents, batch jobs, services) are decomposed into workload units, each getting its own verdict with a consolidation option. An add-capabilities branch (for teams already running agents on AWS) recommends which AgentCore services to enable on any runtime — no runtime scoring. Temporal systems dissolve into the same unit flow — worker polling tiers and Activity execution classes become units (rules in the Temporal decision reference); Workflow orchestration code is never rewritten — never a Step Functions translation. Requires at least one agentic component: a purely non-agent system (only plain services \u002F batch jobs \u002F HTTP endpoints, or a Temporal worker whose Activities are all non-agent) is out of scope — Clarify halts it (scope gate) and points to gcp-to-aws \u002F heroku-to-aws \u002F llm-to-bedrock. Not for: pure compute\u002Fdata migration with no AI agent; pure LLM SDK rewrite without agent architecture (use llm-to-bedrock); or detailed per-model pricing.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4627,4630,4633,4634],{"name":4628,"slug":4629,"type":16},"Agents","agents",{"name":4631,"slug":4632,"type":16},"AI Infrastructure","ai-infrastructure",{"name":21,"slug":22,"type":16},{"name":4635,"slug":4636,"type":16},"Engineering","engineering","2026-08-14T04:51:57.95352",{"slug":4639,"name":4639,"fn":4640,"description":4641,"org":4642,"tags":4643,"stars":26,"repoUrl":27,"updatedAt":4651},"architect-for-startups","advise on AWS architecture for startups","Startup-tailored AWS architecture advice that adjusts recommendations to the company's stage (pre-revenue through Series B+), team size, runway, and available credits. Use when a founder wants guidance or a recommendation rather than code changes: which services to choose, how to plan or review an architecture, how to stretch credits and control cost, or how to prepare architecture for a fundraise or technical diligence. For an interactive discovery flow that scaffolds and writes the architecture into the codebase, use start-building-for-startups. Do not use for: writing or scaffolding code, factual AWS Activate \u002F programs \u002F credits lookups (see knowledge-base-for-startups), a single copy-paste prompt (see prompt-library-for-startups), or migration intent such as GCP-to-AWS or Heroku-to-AWS (see the migration skills: `gcp-to-aws`, `heroku-to-aws`, `llm-to-bedrock`).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4644,4647,4648],{"name":4645,"slug":4646,"type":16},"Architecture","architecture",{"name":21,"slug":22,"type":16},{"name":4649,"slug":4650,"type":16},"Strategy","strategy","2026-08-14T04:27:18.122372",{"slug":4,"name":4,"fn":5,"description":6,"org":4653,"tags":4654,"stars":26,"repoUrl":27,"updatedAt":28},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4655,4656,4657,4658],{"name":21,"slug":22,"type":16},{"name":24,"slug":25,"type":16},{"name":18,"slug":19,"type":16},{"name":14,"slug":15,"type":16},{"slug":4660,"name":4660,"fn":4661,"description":4662,"org":4663,"tags":4664,"stars":26,"repoUrl":27,"updatedAt":4671},"heroku-to-aws","migrate workloads from Heroku to AWS","Migrate workloads from Heroku to AWS. Triggers on: migrate from Heroku, Heroku to AWS, move off Heroku, migrate Heroku app, migrate Heroku Postgres to RDS, migrate Heroku Redis to ElastiCache, migrate Heroku Kafka to MSK, migrate dynos to Elastic Beanstalk, migrate dynos to Fargate, Heroku migration, move from Heroku to AWS, migrate Heroku Private Space, Heroku to Elastic Beanstalk, Heroku to ECS, Heroku to Fargate, leave Heroku, migrate off Heroku platform, what-if workshop, reprice Heroku migration, compare migration scenarios, workshop mode. Runs a 6-phase process: discover Heroku resources live via the authenticated Heroku CLI (read-only, consent-gated) and\u002For from Terraform files, Procfile\u002Fapp.json, and optional billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. After Estimate, an optional what-if workshop can reprice region\u002FHA\u002Fcompute\u002FGraviton scenarios without re-discovery. Clarify must finish before Design, Estimate, or Generate. Uses a flat resource model (no clustering or dependency graphs) with deterministic mapping tables for core services (Dynos → Elastic Beanstalk by default, Postgres → RDS\u002FAurora, Redis → ElastiCache, Kafka → MSK) and a fast-path table for 13+ common add-ons. Cedar\u002FFir generation detection is detect-only in v1. Pipeline\u002FReview Apps are detect-only. Do not use for: GCP or Azure migrations to AWS, AWS-to-Heroku reverse migration, general AWS architecture advice without migration intent, Heroku-to-Heroku refactoring, or multi-cloud deployments that do not involve migrating off Heroku.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4665,4666,4669,4670],{"name":21,"slug":22,"type":16},{"name":4667,"slug":4668,"type":16},"Heroku","heroku",{"name":18,"slug":19,"type":16},{"name":14,"slug":15,"type":16},"2026-08-14T04:52:09.216805",{"slug":4673,"name":4673,"fn":4674,"description":4675,"org":4676,"tags":4677,"stars":26,"repoUrl":27,"updatedAt":4688},"knowledge-base-for-startups","retrieve AWS startup reference content","AWS Startups reference content — Activate FAQ, credits guide, programs, partner offers, sample architectures, and hundreds of learn articles spanning generative AI, cloud architecture, cost optimization, security, fundraising, go-to-market, and real-world startup case studies. Use when the user asks factual questions about AWS Activate (eligibility, credits, programs, providers), wants a sample architecture or solution guide, or needs an AWS-curated learn article on a specific startup topic. For copy-paste AI prompts (RAG chatbot, MVP scaffold, security baseline, GPU quota, etc.), see the prompt-library-for-startups skill. Do not use for: account-specific lookups (credits balance, Activate membership status, application status), real-time event listings beyond the events stub, or content not present in the bundled `references\u002F` tree.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4678,4679,4682,4685],{"name":21,"slug":22,"type":16},{"name":4680,"slug":4681,"type":16},"Cloud","cloud",{"name":4683,"slug":4684,"type":16},"Documentation","documentation",{"name":4686,"slug":4687,"type":16},"Research","research","2026-07-25T05:32:19.312255",{"slug":4690,"name":4690,"fn":4691,"description":4692,"org":4693,"tags":4694,"stars":26,"repoUrl":27,"updatedAt":4706},"llm-to-bedrock","migrate LLM calls to Amazon Bedrock","Use when the user wants to migrate code that calls OpenAI, Gemini\u002FGoogle AI, or the Anthropic API to Amazon Bedrock — a pure model\u002FSDK rewrite. End-to-end: assesses the codebase, then rewrites SDK calls, evaluates output quality against Bedrock, and delivers a ready-to-merge git branch. Not for: agent runtime selection, agentic architecture decisions, or agent migration planning — use agent-advisor for those. Not for standalone Bedrock cost estimates or infrastructure-only migration. The Assess phase is handled by this plugin's own gcp-to-aws skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4695,4696,4699,4702,4703],{"name":21,"slug":22,"type":16},{"name":4697,"slug":4698,"type":16},"Gemini","gemini",{"name":4700,"slug":4701,"type":16},"LLM","llm",{"name":14,"slug":15,"type":16},{"name":4704,"slug":4705,"type":16},"OpenAI","openai","2026-08-14T04:51:58.393797",{"slug":4708,"name":4708,"fn":4709,"description":4710,"org":4711,"tags":4712,"stars":26,"repoUrl":27,"updatedAt":4719},"prompt-library-for-startups","provide AI coding prompts for startups","AWS-curated copy-paste prompts for AI coding agents (MVP scaffolding, RAG chatbot with Claude on Bedrock, security baseline evaluation, cost anomaly detection, GPU quota requests, EKS deployment, Well-Architected review, etc.) plus downloadable installable agents (Multi-Account Transition Advisor, Bill Shock Preventer, Service Quota Agent, Bedrock Model Availability Agent, AWS DB Advisor). Use when the user asks for a prompt to do X on AWS, wants an installable agent for multi-account \u002F cost monitoring \u002F quota management \u002F Bedrock model availability \u002F database selection, or asks how to use AWS prompts. For migration intent (GCP to AWS, OpenAI\u002FGemini to Bedrock), route to the migration skills in this plugin (`gcp-to-aws`, `heroku-to-aws`, `llm-to-bedrock`). Do not use for: factual AWS Activate \u002F programs \u002F credits questions, learn articles, sample architectures, or for prompts that are not in the bundled `references\u002Fprompt-library\u002F` tree.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4713,4714,4717,4718],{"name":21,"slug":22,"type":16},{"name":4715,"slug":4716,"type":16},"Coding","coding",{"name":4635,"slug":4636,"type":16},{"name":4700,"slug":4701,"type":16},"2026-08-14T04:27:16.118669"]