メニュー
Orchestrate the lightweight academic pipeline by chaining paper-fetch, paper-reflect, and paper-normalize.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
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.
Build a lightweight local vector-style index record from normalized paper data.
Normalize extracted paper entities into canonical forms with lightweight audit logs.
Generate a lightweight structured reflection JSON for a single paper record.
| name | paper-workbench |
| description | Orchestrate the lightweight academic pipeline by chaining paper-fetch, paper-reflect, and paper-normalize. |
| metadata | {"openclaw":{"emoji":"🛠️","requires":{"bins":["python3"]}}} |
Use this skill when the user wants a single entrypoint for the current MVP academic pipeline.
Workflow
python3 /root/openclaw-dev/workspace/scripts/run_workbench.py "<query>" --max-results <N> --top-n <M>paper-fetchpaper-reflectpaper-normalizeNotes