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Designs production-grade RAG systems with document chunking, embedding generation, vector store configuration, hybrid search pipelines, reranking, and retrieval quality evaluation.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
Build, audit, and improve harnesses that make AI coding agents reliable: AGENTS.md/CLAUDE.md instruction files, feature/state tracking, verification gates, scope boundaries, session handoff, memory persistence, context budgets, tool-permission safety, and multi-agent coordination. Use this whenever a coding agent is unreliable across sessions — forgets context, drifts out of scope, claims "done" before tests pass, or starts each session inconsistently — or when creating or assessing AGENTS.md, CLAUDE.md, feature_list.json, init.sh, progress.md, or session-handoff files. Reach for it even if the user never says the word "harness."
Generate a consolidated digest from multiple information sources
Track and report on progress toward defined goals
Review the agent's own recent outputs for quality and accuracy
Generate changelogs from recent commits and merged PRs
Implement features on branches from issue descriptions
SOC 직업 분류 기준
| name | rag-architect |
| description | Designs production-grade RAG systems with document chunking, embedding generation, vector store configuration, hybrid search pipelines, reranking, and retrieval quality evaluation. |
| metadata | {"sources":[{"kind":"github-file","repo":"jeffallan/claude-skills","path":"skills/rag-architect/SKILL.md","commit":"3bf9a24b76a7c122f1fc05e83929fbc84e1c207a","attribution":"Jeffallan","license":"MIT","usage":"referenced"}]} |
