ロールバックと保存の証明を必要とするスキーマ、データ、API、プロトコル、設定、依存関係の移行において、後方互換性のある安全なトランジションを実装します。
このスキルは、開発者やAIエージェントが、複数のシステム間でのデータ、スキーマ、API、プロトコル、設定、依存関係などの移行を安全かつ可逆的に行うためのガイドラインを提供します。主な目的は、ダウンタイムやデータ損失のリスクを最小限に抑え、移行中も新旧両方のシステムが共存できるようにすることです。 スキルは、移行を順次実行するアプローチ（Expand-Migrate-Contractパターンなど）を推奨し、フォワードパス（新しい状態への移行）とロールバックパス（古い状態への復帰）の両方を定義することを必須としています。また、データの破壊的な変更は明示的に分離し、承認を必要とすること、移行の進行中は新旧両方のバージョンが安全に動作できるようにすること、再試行が冪等であること、部分的な障害が観測可能であることを要求します。 現在の読者（リーダー）と書き手（ライター）、データ構造、互換性ウィンドウ、所有権を明確にした上で編集作業を開始するよう促し、移行の各段階で新旧両方のパスを検証することを推奨します。最後に、要求された段階が完了したら処理を停止し、後続の破壊的な収縮段階を暗黙的に実行しないことを強調しています。
npx skills add https://github.com/JuliusBrussee/caveman/tree/main/skills/migration編集を開始する前に、現在のリーダー、ライター、データ構造、互換性ウィンドウ、所有権をマッピングします。
要求された段階が完了したら停止し、後続の破壊的な収縮を暗黙的に実行しないでください。
This repo contains 12 individual skills — each has its own dedicated page.
Find and label every LLM workflow in the repository so Caveman Cloud groups spend by workflow instead of one bucket. Use for "discover workflows" or breaking LLM spend down by workflow.
Read-only review of Caveman Cloud evidence: cost, Cave Score, workflows, traces, latency, errors, routing, savings. Use when asked what Caveman found or where LLM spend goes.
Read-only repository explorer for cold-start orientation, broad cross-file localization, or when a direct search failed. Skip it when the exact file or symbol is already named. Returns path:line citations only; its reads stay out of main context.
Act on a Caveman learn report - review the ranked token sinks, apply cost-lowering fixes with per-edit consent, and report what those fixes returned. Use when asked to lower an agent's token cost, what caveman has saved, to trim a heavy CLAUDE.md, or to offload re-pasted context into cavemem.
Inspect Caveman Cloud's experiment lifecycle and block unsafe execution. Use when asked to start, approve, cancel, promote or roll back a Caveman experiment.
Turn a Caveman optimization observation into an operator-chosen candidate with a paired baseline evaluation. Use when asked to inspect or evaluate a Caveman optimization report. Needs explicit approval.
Wire a repository through the Caveman Cloud gateway so every LLM request is measured, with no behavior change. Use for "set up caveman" or adding LLM spend observability.
Diagnose ambiguous failures before editing. Use for unknown causes, intermittent behavior, performance regressions, or investigations needing evidence-ranked hypotheses.
Build feature work with high overbuilding risk. Use for new behavior, product slices, or integrations where repository reuse, strict scope, and an explicit stop condition matter.
Restructure code while preserving behavior. Use for extraction, consolidation, ownership moves, or cleanup where verification must bracket structural edits.
Fix bugs and small behavior changes at the narrowest responsible layer. Use when regression proof, preserved surrounding behavior, and task-relevant tests matter.
Prove existing work meets acceptance conditions without expanding scope. Use for validation-only tasks, completion checks, focused gate runs, and last-mile proof.
ElevenLabs text-to-speech with mac-style say UX.
Oracle CLI second-model review/debug/refactor/design with selected files, dry-run token checks, API or browser engine.
Capture and automate macOS UI with the Peekaboo CLI.
Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
Build a throwaway prototype to flesh out a design — a runnable terminal app for state/business-logic questions, or several radically different UI variations toggleable from one route.
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".