| name | paper-workbench |
| description | Researcher-profile-driven paper intake and literature workbench for academic workflows. Use whenever the user wants to skim, deep-read, card, compare, synthesize, map research gaps, or build a literature review from papers, arXiv/AlphaXiv links, DOIs, PDFs, or existing workbench artifacts. Trigger even when the user only says “精读这篇”, “整合这几篇”, “找研究空白”, or “搭综述框架”.
|
| category | research-learning-knowledge |
| tags | ["paper","research","normalization","literature-review","synthesis","doi","arxiv","analysis"] |
| version | 1.1.0 |
| argument-hint | [paper-source-or-artifact] [--mode scan|deep-read|card|synthesis|review|json|interpret|xray] [--workspace PATH] [--profile PATH] [--save PATH] [--lang LANG] [--fulltext auto|prefer|never] |
| allowed-tools | Read, Write, WebFetch, Bash(curl *), Bash(python *), Bash(pytest *) |
Paper Workbench
Unified entrypoint for paper intake, strategic reading, multi-paper synthesis,
and review construction.
Keep paper-record as the normalization layer. Do not merge high-level
analysis back into the normalized record.
In the python commands below, <skill-dir> is this skill's base directory,
announced when the skill loads. Substitute that literal path; it is not an
environment variable. Bundled scripts self-locate, so only the path needs to
resolve.
When to use
Use this skill when the job is to:
- read one paper quickly
- deeply deconstruct one paper
- compare or synthesize multiple papers
- build a review outline or gap map
- normalize paper sources into reusable machine-readable artifacts
Do not use this skill when the primary job is to implement a paper from its
methods into working code. That implementation work is out of scope for this
skill.
Public interfaces
paper-record — normalized single-paper factsresearcher-profile — user research anchorpaper-deep-read — single-paper strategic analysis artifactliterature-synthesis — cross-paper integration artifactreview-outline — literature-review planning artifact
Accepted inputs
- arXiv IDs and arXiv URLs
- AlphaXiv URLs
- DOI strings or
doi.org/... URLs
- local academic PDFs or text files
- remote PDF URLs
- paper landing pages that expose a PDF
- existing
paper-record JSON
- existing
researcher-profile, paper-deep-read, literature-synthesis, or
review-outline JSON
Routing workflow
- Resolve the input class from
$ARGUMENTS, the latest user message, or a
pasted JSON artifact.
- If the request is paper-level and not already normalized, run
scripts/normalize_paper.py first.
- Determine the mode from explicit user intent or the defaulting rules below.
- If the chosen mode is profile-sensitive, load the supplied
researcher-profile or collect only the missing fields.
- Produce the requested mode output.
