agentmods.dev

serverless-migration-advisor

An advisor for moving always-running AWS workloads, such as EC2, ALB, ECS, or RDS systems, toward serverless and Spot patterns. Serverless services run on demand, while Spot capacity trades a lower price for possible interruption.

In plain words
What is it for?
Use it to plan AWS migrations involving EC2-to-Lambda, ALB-to-API-Gateway, batch jobs on Spot, event-driven systems, or cost-reduction efforts.
Why use it?
It helps classify a workload and assess whether a proposed migration fits its runtime, frequency, and data needs. It also highlights trade-offs and cases where evidence is limited.

Skill for Claude CodeCodex

21 1mo ago A scan 121 tokens original MIT
View the source file roboco-io/plugins
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/roboco-io/plugins/serverless-migration-advisor
Any agent
npx skills add roboco-io/plugins --skill serverless-migration-advisor
Clone the repo
git clone --depth 1 https://github.com/roboco-io/plugins

Made for: Claude Code, Codex.

Per session 121 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,237 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00121 $0.03237
Opus 5 $0.00060 $0.01618
Sonnet 5 $0.00024 $0.00647
Haiku 4.5 $0.00012 $0.00324

Measured 2d ago against content hash 3a112c8faa1d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

serverless-migration-advisor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/workflow/skills/serverless-migration-advisor/SKILL.md · 227 lines

How it starts

The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Serverless Migration Advisor

Role: 기존 AWS 워크로드(EC2/ALB/ECS/RDS/모놀리스)를 서버리스+Spot 패턴으로 이행할 때의 업스트림 어드바이저. 워크로드 분류 → 트레이드오프 평가 → 타겟 아키텍처 매핑 → 단계별 이행 계획 생성을 담당한다. 구현 how-to는 후속 스킬로 위임한다.

이 스킬이 아닌 것

  • aws-well-architected: 기존 아키텍처의 Pillar 준수 리뷰 — 본 스킬은 이행에 집중한다.
  • 실시간 AWS 요금 계산기 아님. 검증 사례 기반의 비용 범위만 인용한다.
  • Terraform/CDK 생성기 아님. 스니펫과 체크리스트까지만 제공한다.
  • 멀티클라우드 아님. AWS 전용이다.
  • 구현 how-to 아님. 타겟 확정 후 sagemaker-spot-training 등으로 위임한다.

언제 사용하나

트리거 키워드: 서버리스 이행, EC2에서 Lambda로, Spot 이행, ALB에서 API Gateway, 월 비용 절감 이행, serverless migration, batch on Spot, 콜드 스타트 이행.

실행 순서 (5 Phase)

Phase 1 — Workload Classification (항상 실행)

interview-bank.md §Phase 1의 Q1-Q4 JSON을 AskUserQuestion으로 순차 호출한다:

  • Q1 Workload type: 배치/훈련 / 상시 API / ETL / 이벤트 기반 / 모놀리스(Tier 3)
  • Q2 Current environment
  • Q3 Execution frequency
  • Q4 Single run duration

응답으로 Tier(1/2/3) + sub-type을 결정한다. 예: Tier 1 / ML training / daily / 8h.

Tier 3 응답이 하나라도 있으면 즉시 Branch E 안내문을 표시한다:

⚠️ Tier 3 이행은 검증 사례 없음. 원칙 수준 가이드와 AWS 공식 링크만 제공됩니다. 파일럿 필수. patterns-tier3-monolith.md 및 patterns-tier3-data.md 참조.

Phase 2 — IaC Scan (선택)

사용자가 IaC 파일 경로(Terraform .tf, CDK .ts/.py, CloudFormation .yaml)를 제공하면:

  1. Glob으로 파일 목록 획득
  2. Read + 정규식 기반 리소스 추출 (첫 버전 한계: resource "aws_...", CDK L2 construct 이름 패턴)
  3. 현 아키텍처 요약 테이블 생성 (인스턴스 타입·개수·월 비용 추정 범위)

IaC가 없거나 사용자가 스킵을 선택하면 Phase 3로 넘어간다.

IaC 파서 한계: 정규식 기반은 참조 추출만 지원한다. 상호 참조·변수 치환·module 재귀는 미지원이다. 깊은 분석이 필요하면 수동 입력을 요청한다.

Phase 3 — 제약·리스크 심층 인터뷰

Phase 1 Q1 응답에 따라 interview-bank.md §Phase 3의 분기 중 하나를 실행한다:

  • Branch A (Batch/Training): A1 Spot 허용도 / A2 wall-clock / A3 체크포인트
  • Branch B (Always-on API): B1 콜드 스타트 p99 / B2 지속 연결 / B3 트래픽 패턴
  • Branch C (ETL): C1 데이터 볼륨 / C2 지속 시간 / C3 상태 저장소
  • Branch D (Event-driven): D1 이벤트 소스(multiSelect) / D2 순서 보장 / D3 중복 허용
  • Branch E (Monolith / Tier 3): E1 bounded context 식별 단계 / E2 다운타임 / E3 데이터 일관성

Read the full file on GitHub · 227 lines

Files

What ships with it

13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 227 lines · 121 tokens per session scan A 3a112c8faa1d

Subscribe to this mod's changes

serverless-migration-advisor is a skill published in the GitHub repository roboco-io/plugins (21 stars, last pushed 1mo ago), licensed MIT. It adds 121 tokens to every session and 3,237 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Backend and APIsDevOps and cloudPlanning
Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

agent-host-chat-contributions

Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.

microsoft/vscode · 56 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens