以高過度建置風險完成功能開發。適用於新建行為、產品片段或整合工作，重視儲存庫重複使用、嚴格的範圍與明確的停止條件。
這個技能「lean-build」是一個專門為「Native Core」架構設計的開發規則集，旨在引導 AI 代理以簡潔、精確且避免過度工程的方式實作功能。它要求代理從請求與現有儲存庫中推導出具體的可觀察驗收條件與明確的非目標，並識別出貫穿各層級的進入點及其負責的不變量。其核心價值在於：交付一個橫跨相關層級的連貫端到端路徑，而非將所有工作塞入單一檔案或直接修補。技能也強調「重複使用合適的接縫」，並在修補導致重複行為、削弱所有權或隱藏根本原因時進行重構。此外，它嚴格限制模式的引入、供應商、配置、可擴展性與打磨，除非驗收條件明確要求。該技能適用於任何支援 SKILL.md 的 AI 代理平台（如 Claude Code、Cursor、Codex），並透過規則引導代理在正確的約束下進行開發，最終在驗收條件通過時停止，僅報告實質的遺漏與觸發條件。
npx skills add https://github.com/JuliusBrussee/caveman/tree/main/skills/lean-buildNative Core 以架構優先的簡潔性仍是強制要求。將功能轉化為符合系統的完整、狹義成果。
執行路徑。執行聚焦的驗證。在驗收條件通過時停止。僅報告實質的遺漏與觸發條件。
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.
Implement reversible compatibility-safe transitions. Use for schema, data, API, protocol, configuration, or dependency migrations requiring rollback and preservation proof.
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".