Full Codebase Migrator

SkillFiles & storage

Uses 1M context window to ingest an entire codebase and output a file-by-file migration plan. Supports JS to TS, React class to hooks, framework migrations, and more. Generates migration-plan.md with file inventory, dependency graph, migration order, file-by-file changes, estimated effort, and risk assessment.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Full Codebase Migrator skill

What this skill tells your AI

The instructions your AI receives, as published by onewave-ai/claude-skills in full-codebase-migrator/SKILL.md and read by ahel’s review.

Leverage the full 1M token context window to ingest an entire codebase, understand its architecture end-to-end, and produce a comprehensive, file-by-file migration plan that a team can execute sequentially without conflicts.

Contents

  • references/migration-types.md -- supported migration types; when to use and when not to use this skill.
  • references/ingestion.md -- architecture, glob patterns, metadata collection, read order, context budgeting, and dependency graph construction (Steps 0-2).
  • references/workflow-detail.md -- per-file assessment, migration order, risk scoring, and effort estimation templates (Steps 3-6).
  • references/output-template.md -- migration-plan.md and migration-plan.json templates, edge cases, and the final quality checklist (Steps 7-8).

Workflow

  1. Identify scope. Determine migration type, scope (full repo or directory), output location for migration-plan.md, and any exclusions or constraints. Infer from the user's prompt when already specified. See references/migration-types.md for supported types and fit.
  2. Ingest the codebase. Glob all source files, collect metadata with Bash (line counts, package manifest, configs, git history, directory tree), then Read every source file. For 500+ file codebases, dispatch Agent sub-agents to read directory subtrees in parallel. See references/ingestion.md.
  3. Build the dependency graph. Extract every import, build an adjacency list, classify each file into layers, detect circular dependencies, and classify external dependencies. See references/ingestion.md.
  4. Assess each file. Produce a per-file migration assessment covering layer, complexity, patterns found, required changes, prerequisite dependencies, risk factors, and testing impact. See references/workflow-detail.md.
  5. Calculate migration order. Run a topological sort by layer, apply practical adjustments (quick wins, high-risk-early, break cycles first), and group files into buildable, PR-sized phases. See references/workflow-detail.md.
  6. Assess risk. Score each file 1-5 on complexity, centrality, volatility, test coverage, and external coupling. Build the migration-level risk matrix and rollback strategy. See references/workflow-detail.md.
  7. Estimate effort. Derive per-file, per-phase, and total estimates with overhead and a 20% buffer, then translate into calendar time by team size. See references/workflow-detail.md and the effort calibration table in references/migration-types.md.
  8. Generate the deliverable. Write migration-plan.md to the output location, and migration-plan.json when machine-readability helps. Verify against the quality checklist before delivering. See references/output-template.md.

Edge Cases

Codebases too large for context, monorepos, partially migrated codebases, and codebases without tests each need adjusted handling. See references/output-template.md.

Signals

GitHub stars
291
Forks
46
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
full-codebase-migrator
Source
github.com/onewave-ai/claude-skills