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Cloud workload complexity scorer

Scores an application's cloud migration complexity across seven weighted dimensions, assigns a Low/Medium/High complexity tier with transparent reasoning, and recommends the appropriate 7Rs migration strategy plus…

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Purpose

Turn an application's technical and organizational attributes into a defensible migration complexity tier (Low/Medium/High) with a recommended 7Rs strategy, effort estimate, and ranked risks — so migration leads can sequence waves, size effort, and defend disposition decisions without relying on gut feel.

When to Use

Invoke this skill when the user asks to:

  • Score or assess the migration complexity of a specific application
  • Decide which of the 7Rs (Retire, Retain, Rehost, Relocate, Repurchase, Replatform, Refactor) to apply to a workload
  • Prioritize or sequence a portfolio of apps into migration waves
  • Estimate effort and risk for moving an app to AWS, Azure, or GCP
  • Compare two or more candidate applications to decide which to migrate first
  • Justify a disposition decision to stakeholders with structured reasoning

Inputs Required

Before starting, collect:

  • Application name and function: What the app does and its business criticality
  • Architecture type: Monolith / N-tier / microservices / serverless / mainframe / packaged (COTS)
  • Dependencies: Upstream/downstream systems, shared databases, middleware, integrations, licensing constraints
  • Data profile: Volume, data sensitivity classification (public / internal / confidential / regulated), and statefulness
  • Compliance requirements: Applicable regimes (e.g., PCI-DSS, HIPAA, GDPR, SOX, FedRAMP) and data residency constraints
  • Team skills: Team's cloud maturity and familiarity with the target platform and app's tech stack
  • Target cloud and timeline: Destination platform and any hard deadline or business driver

If data sensitivity or team skill level is not provided, assume "confidential" and "moderate cloud maturity" respectively and note the assumption in the output.

Instructions

Step 1: Score the Seven Complexity Dimensions

Rate each dimension 1 (low complexity) to 5 (high complexity). Anchor each score to concrete criteria — do not assign scores without stated reasoning.

Dimension 1 — Architecture Coupling (weight 20%)

  • 1–2: Stateless, cleanly layered, containerizable as-is
  • 3: N-tier monolith with clear boundaries
  • 4–5: Tightly coupled monolith, mainframe, or COTS with no clean seams
  • Key signal: Can components be moved independently?

Dimension 2 — Dependency Complexity (weight 20%)

  • 1–2: Few, well-documented, loosely coupled integrations
  • 3: Several integrations, some shared services
  • 4–5: Shared databases, undocumented integrations, hard licensing locks, or synchronous chains that must move together
  • Key signal: How many things break if this moves alone?

Dimension 3 — Data Gravity & Statefulness (weight 15%)

  • 1–2: Small, stateless, or easily replicated data
  • 3: Moderate volume with manageable sync
  • 4–5: Large datasets, high transaction rates, or state that cannot tolerate downtime
  • Key signal: Cost and risk of moving the data itself

Dimension 4 — Data Sensitivity & Compliance (weight 15%)

  • 1–2: Public/internal data, no regulatory regime
  • 3: Confidential data, standard controls
  • 4–5: Regulated data (PHI, PCI, PII under strict regimes), data residency mandates, or audit requirements
  • Key signal: Does compliance dictate architecture or region?

Dimension 5 — Operational & Business Criticality (weight 10%)

  • 1–2: Non-critical, tolerant of downtime
  • 3: Business-important, defined maintenance windows
  • 4–5: Mission-critical, tight RTO/RPO, 24/7 SLA
  • Key signal: Blast radius of a failed migration

Dimension 6 — Team Skill Gap (weight 10%)

  • 1–2: Team fluent in target platform and app stack
  • 3: Familiar with one, learning the other
  • 4–5: New to both cloud-native patterns and the app's technology
  • Key signal: Execution risk from capability gaps

Dimension 7 — Technical Debt & Documentation (weight 10%)

  • 1–2: Modern stack, well documented, active maintainers
  • 3: Some legacy, partial documentation
  • 4–5: End-of-life runtimes, no docs, no owning team
  • Key signal: How much discovery work is unknown

Step 2: Calculate the Weighted Complexity Score

Compute the weighted score: sum of (dimension score × weight), producing a value from 1.0 to 5.0.

Assign the tier:

  • Low: 1.0 – 2.3
  • Medium: 2.4 – 3.6
  • High: 3.7 – 5.0

Override rule: any single dimension scoring 5 on Dependency Complexity, Data Sensitivity & Compliance, or Architecture Coupling automatically floors the tier at Medium regardless of the weighted average — flag this explicitly.

Step 3: Recommend the 7Rs Strategy

Map the profile to the most appropriate 7Rs disposition, with a one-sentence rationale and a stated trade-off:

  • Retire: No longer used or redundant with another system
  • Retain: Not worth moving now (regulatory, EOL soon, or dependency-blocked)
  • Rehost (lift-and-shift): Low coupling, low skill gap, speed-driven — fastest, least optimized
  • Relocate: Move existing virtualization (e.g., VMware) to cloud-hosted equivalent with minimal change
  • Repurchase: COTS app with a viable SaaS replacement
  • Replatform (lift-tinker-shift): Moderate complexity where targeted changes (managed DB, container) yield outsized benefit
  • Refactor: High business value plus high architectural debt where cloud-native rebuild is justified

State the primary recommendation and, when the profile is borderline, name the runner-up and the condition that would flip the decision.

Step 4: Effort Estimate and Migration Wave Placement

  • Effort band: T-shirt size (S / M / L / XL) tied to the tier and chosen strategy
  • Rough duration: Weeks range for a typical team
  • Wave recommendation: Early wave (Low complexity, builds momentum) / Middle wave / Late wave (High complexity, dependency-heavy) — with the reason

Step 5: Top Risks and Prerequisites

List the 3–5 highest risks ranked by severity, each with a concrete mitigation. Then list any prerequisites (discovery, dependency mapping, compliance sign-off) that must complete before migration begins.

Output Format

  • Structure: Scoring table → weighted score and tier → 7Rs recommendation → effort/wave → ranked risks and prerequisites
  • Length: 600–900 words
  • Format: A dimension-by-dimension scoring table (dimension, score 1–5, weight, one-line reasoning) followed by structured prose and ranked bullet lists
  • Sections: Complexity Scoring Table → Weighted Score & Complexity Tier → Recommended 7Rs Strategy → Effort Estimate & Wave Placement → Top Risks & Mitigations → Prerequisites
  • Tone: Enterprise architect — analytical, decisive, and transparent about trade-offs; every score carries a reason

Quality Checklist

Before delivering output, verify:

  • [ ] All seven dimensions are scored 1–5 with a stated reason for each score
  • [ ] The weighted score is arithmetically correct and maps to the stated tier band
  • [ ] The override rule was checked and flagged if triggered
  • [ ] Exactly one primary 7Rs strategy is recommended, with rationale and trade-off
  • [ ] Effort band and wave placement are both assigned and justified
  • [ ] Between 3 and 5 risks are listed, each ranked and paired with a specific mitigation
  • [ ] Any assumed inputs (default data sensitivity or skill level) are explicitly noted

Notes

  • Dependency complexity is the most common reason migrations slip — when dependencies are undocumented, recommend a discovery phase before committing to a strategy.
  • Rehost is the default for speed, but a Medium-tier app with a managed-service opportunity often justifies Replatform for lower long-term operational cost; call this out when relevant.
  • Compliance and data residency can override the "cheapest path" — a regulated workload may require Refactor or a specific region even when the score suggests Rehost.
  • When scoring a portfolio, keep dimension weights consistent across all apps so tiers remain comparable for wave sequencing.

How to use this skill

This file is a Claude Code skill in Anthropic's standard format — markdown with YAML frontmatter at the top.

Installing in Claude Code:

  • ~/.claude/skills/<folder-name>/SKILL.md — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)
  • <your-project>/.claude/skills/<folder-name>/SKILL.md — auto-loads only when working in that project (recommended for project-specific skills)

Restart Claude Code or open a new session to register.

Using in Claude.ai, ChatGPT, Gemini, or other AI tools:

  1. Drag this file into a new chat, or copy and paste its contents
  2. Send your task or request as your next message — the AI will apply the skill where it fits

For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills