debugging-investigator은(는) 무엇을 하나요?
alphasafal/production-agent-skills에서 가져온 에이전트 스킬 '디버깅 조사관'입니다.
에이전트 스킬 '디버깅 조사관'으로, alphasafal/production-agent-skills에서 가져왔습니다.
이 스킬은 AI 에이전트가 코드 디버깅 문제를 체계적으로 조사하고 분석할 수 있도록 설계되었습니다. 주로 Claude Code, Cursor, Codex와 같은 개발 환경에서 사용되며, 복잡한 버그나 오류를 단계별로 추적하고 근본 원인을 식별하는 데 도움을 줍니다. '디버깅 조사관'은 일반적인 디버깅 워크플로우를 자동화하여, 에이전트가 로그 분석, 스택 트레이스 검토, 조건부 중단점 설정 등을 수행하도록 안내합니다. 이를 통해 개발자는 반복적인 디버깅 작업에서 벗어나 더 창의적인 문제 해결에 집중할 수 있습니다. 이 스킬은 alphasafal/production-agent-skills 리포지토리의 일부로, 주로 JavaScript/TypeScript, Python 등의 언어와 Node.js, React 같은 프레임워크에서 활용됩니다.
npx skills add https://github.com/alphasafal/production-agent-skills/tree/main/skills/debugging-investigatorInstalled? Explore more 코딩 & 개발 skills: steipete/bluebubbles, steipete/eightctl, steipete/blucli · View all 6 →
alphasafal/production-agent-skills에서 가져온 에이전트 스킬 '디버깅 조사관'입니다.
This repo contains 7 individual skills — each has its own dedicated page.
Runs an end-to-end structured tabular data science workflow: problem framing, schema/leakage/missingness checks, EDA, baseline before modeling, feature engineering, model comparison against the baseline, and error/slice analysis. Use when asked to analyze a dataset, build a predictive model, evaluate a model's performance, or investigate a data quality issue in tabular data. Do not use for pure data engineering/ETL with no analysis or modeling question, for unstructured data (images/audio/free text at scale) without a tabular framing, or when the task is answerable by a single summary statistic with no need for the full workflow — say so and just answer it.
Agent skill 'feature-to-production' from alphasafal/production-agent-skills.
Agent skill 'production-code-review' from alphasafal/production-agent-skills.
Agent skill 'product-manager' from alphasafal/production-agent-skills.
Agent skill 'repo-architect' from alphasafal/production-agent-skills.
Turns research into an auditable technical or product decision: defines the decision and constraints, gathers evidence with sources, separates evidence from assumption, compares alternatives against explicit criteria, and produces an ADR. Use when choosing between technologies/approaches ("Kafka vs SQS", "build vs buy"), documenting the reasoning behind a decision already made, or when asked to "research this and recommend one." Do not use for implementing the chosen option (that's a separate skill), or for open-ended research with no decision to make at the end.
Agent skill 'system-design-reviewer' from alphasafal/production-agent-skills.
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.