手術級修補
若經濟可行，優先重現失敗；否則收集最強可得的證據。
- 將症狀追溯至負責機制。
- 變更擁有錯誤行為的最狹窄層級。
- 保留不相關的行為與使用者變更。
- 避免在修復之外進行清理、重新命名或抽象化。
- 僅新增與任務相關的回歸驗證。
執行集中驗證加上最近受影響的閘門。在錯誤修復且回歸驗證通過時停止。
精準修復錯誤與微小行為變更，專注於最狹窄的責任層級。適用於需要回歸驗證、保留周圍行為及任務相關測試的情境。
此技能旨在協助開發者以最小影響的方式修復錯誤或進行微小行為修改，確保不干擾既有功能與使用者變更。其核心原則為「在可負擔的情況下優先重現失敗，否則收集最強可得的證據」，從症狀追蹤至負責機制，並變更擁有錯誤行為的最狹窄層級。支援任何程式碼庫，尤其適用於需要嚴謹回歸測試的任務。透過精確定位問題根源，避免不必要的重構、重新命名或抽象化，僅新增任務相關的回歸測試。技能要求執行集中驗證與鄰近受影響閘門，直到錯誤修復且回歸測試通過。
npx skills add https://github.com/JuliusBrussee/caveman/tree/main/skills/surgical-patchInstalled? Explore more 程式設計與開發 skills: steipete/bluebubbles, steipete/eightctl, steipete/blucli · View all 6 →
若經濟可行，優先重現失敗；否則收集最強可得的證據。
執行集中驗證加上最近受影響的閘門。在錯誤修復且回歸驗證通過時停止。
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.
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.
Prove existing work meets acceptance conditions without expanding scope. Use for validation-only tasks, completion checks, focused gate runs, and last-mile proof.
Send and manage iMessages via BlueBubbles, including attachments, tapbacks, edits, replies, and groups.
Control Eight Sleep pods (status, temperature, alarms, schedules).
BluOS CLI (blu) for discovery, playback, grouping, and volume.
Create, search, and manage Bear notes via grizzly CLI.
Capture frames or clips from RTSP/ONVIF cameras.
Search GIF providers with CLI/TUI, download results, and extract stills/sheets.