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Build a lightweight local vector-style index record from normalized paper data.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Build, query, and visualize literature relationship clusters using Kuzu and Cypher.
Fetch paper metadata from lightweight academic sources like arXiv and save normalized paper JSON records.
Write lightweight graph edges from normalized paper entities into a local graph store.
Normalize extracted paper entities into canonical forms with lightweight audit logs.
Generate a lightweight structured reflection JSON for a single paper record.
Orchestrate the lightweight academic pipeline by chaining paper-fetch, paper-reflect, and paper-normalize.
| name | paper-index |
| description | Build a lightweight local vector-style index record from normalized paper data. |
| metadata | {"openclaw":{"emoji":"🗂️","requires":{"bins":["python3"]}}} |
Use this skill after paper-normalize when the user wants the paper added to the lightweight retrieval index.
Workflow
python3 /root/openclaw-dev/workspace/scripts/index_paper.py <normalized_json_path>/root/openclaw-dev/workspace/data/index/vector_index.jsonlNotes