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Orchestrate the lightweight academic pipeline by chaining paper-fetch, paper-reflect, and paper-normalize.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
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