모호한 실패를 진단하여 편집 전에 증거 기반 가설을 수립합니다. 알 수 없는 원인, 간헐적 동작, 성능 저하 또는 증거 기반 가설이 필요한 조사에 사용합니다.
이 스킬은 개발자가 코드를 변경하기 전에 먼저 증거를 수집하고 분석하도록 유도합니다. 관찰된 증상과 추론된 원인을 분리하고, 입력, 상태 전환, 소유권 경계 및 실패 출력을 추적합니다. 가설을 증거와 저렴한 반증 가치에 따라 순위를 매기며, 하나의 신뢰할 수 있는 메커니즘이 모든 증거를 설명할 때까지 코드를 편집하지 않습니다. 원인의 이름을 밝히거나 정확한 차단 요소를 식별할 수 있을 만큼 증거가 충분해지면 탐색을 중단합니다. Claude Code, Cursor, Codex와 같은 AI 에이전트 플랫폼에서 사용할 수 있어, 디버깅 및 조사 작업의 체계성과 신뢰성을 높여줍니다.
npx skills add https://github.com/JuliusBrussee/caveman/tree/main/skills/investigate-firstInstalled? Explore more 코딩 & 개발 skills: steipete/bluebubbles, steipete/eightctl, steipete/blucli · View all 6 →
제품 코드를 변경하기 전에 증거를 수집하세요.
원인과 증거를 보고하세요. 작업이 구현을 승인하지 않는 한 수정하지 마세요.
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.
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.
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.
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.