跳到正文
cccskills
免费在 GitHub 公开

full-codebase-migrator

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.

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(5)

  • SKILL.md3.3 KB
  • references/ingestion.md4.3 KB
  • references/migration-types.md1.6 KB
  • references/output-template.md6.3 KB
  • references/workflow-detail.md6.5 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Full Codebase Migrator

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.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.

中文简介正在准备中。当前显示原文说明。

OneWave-AI/claude-skills3582026年10月20日 更新

Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.

中文简介正在准备中。当前显示原文说明。

OneWave-AI/claude-skills3582026年10月20日 更新

Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.

中文简介正在准备中。当前显示原文说明。

OneWave-AI/claude-skills3582026年10月20日 更新

Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.

中文简介正在准备中。当前显示原文说明。

OneWave-AI/claude-skills3582026年10月20日 更新

Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.

中文简介正在准备中。当前显示原文说明。

OneWave-AI/claude-skills3582026年10月20日 更新

Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.

中文简介正在准备中。当前显示原文说明。

OneWave-AI/claude-skills3582026年10月20日 更新

查看 OneWave-AI 的全部技能

报告此技能的问题