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paper-review
by
helloml0326
· GitHub ↗
· v1.0.0
· MIT-0
265
Downloads
0
Stars
2
Active Installs
1
Versions
Install in OpenClaw
/install paper-review
Description
Review academic papers for correctness, quality, and novelty using OpenJudge's multi-stage pipeline. Supports PDF files and LaTeX source packages (.tar.gz/.z...
Usage Guidance
This skill is plausible for reviewing papers, but exercise caution before using it: (1) It requires model API keys (e.g., OPENAI_API_KEY / ANTHROPIC_API_KEY) though the registry didn't declare them — the keys will allow external model providers to receive your paper content. (2) SKILL.md asks you to pip install third-party packages (py-openjudge, litellm, pypdfium2); install them only in an isolated virtualenv and inspect their source or PyPI page first. (3) No code is bundled with the skill — the instructions expect external software. If you plan to review unpublished/confidential papers, do not provide API keys or upload files until you verify the upstream packages and their privacy policies. Consider asking the publisher/author for a local/offline reviewer tool or requesting the skill author provide source code or a trusted homepage before installing.
Capability Analysis
Type: OpenClaw Skill
Name: paper-review
Version: 1.0.0
The skill bundle provides a legitimate and well-documented tool for academic paper review using the OpenJudge pipeline. It includes detailed instructions for the AI agent on model selection, error handling, and configuration, utilizing standard libraries like litellm and pypdfium2. While the documentation references non-existent model versions (e.g., 'gpt-5.2' and 'claude-opus-4-6') and a future timestamp, these appear to be placeholders or future-dated examples rather than malicious indicators. There is no evidence of data exfiltration, unauthorized command execution, or harmful prompt injection in SKILL.md or reference.md.
Capability Assessment
Purpose & Capability
The name/description (academic paper review) aligns with the runtime instructions (multi-stage review, BibTeX checks). However the skill is instruction-only and assumes third-party packages (py-openjudge, litellm, pypdfium2) and external model providers; the registry metadata does not declare these dependencies or primary credentials, which is a mismatch between the declared package and what the instructions require.
Instruction Scope
SKILL.md explicitly tells the agent/user to install and run an external Python package (python -m cookbooks.paper_review) and to provide files and API keys. It does not instruct reading unrelated files or system secrets, but it will read the entire paper (PDF or TeX package) and send it to external model APIs for multimodal processing — this is within the stated purpose but has privacy implications for unpublished/confidential papers.
Install Mechanism
There is no install spec in the registry (lowest disk-write risk), but SKILL.md instructs pip installing py-openjudge, litellm, and optionally pypdfium2 from PyPI. Installing arbitrary PyPI packages can execute third-party code on the user's machine — moderate risk. The packages referenced are plausible for the described functionality, but the skill does not bundle or vet them.
Credentials
Although the tool legitimately needs model API keys (OPENAI_API_KEY, ANTHROPIC_API_KEY, etc.), the registry declares no required env vars or primary credential. SKILL.md asks for these keys and for an optional CrossRef email. The mismatch (registry declaring no creds while instructions require sensitive API keys) is a proportionality and transparency concern. Also, providing these keys means user data (paper contents) will be sent to the chosen model provider.
Persistence & Privilege
The skill does not request always:true, does not require system config paths, and does not modify other skills. It is user-invocable only and does not demand persistent elevated privileges.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install paper-review - After installation, invoke the skill by name or use
/paper-review - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the paper-review skill.
- Provides multi-stage academic paper review using OpenJudge's PaperReviewPipeline.
- Supports PDF and LaTeX sources for 10 disciplines, with optional BibTeX/reference verification.
- Includes safety checks, correctness analysis, review scoring (1–6), criticality assessment, and BibTeX cross-checks.
- Vision mode enabled by default for PDF input using supported multimodal models.
- Highly configurable via CLI flags for discipline, venue, language, instructions, and more.
Metadata
Frequently Asked Questions
What is paper-review?
Review academic papers for correctness, quality, and novelty using OpenJudge's multi-stage pipeline. Supports PDF files and LaTeX source packages (.tar.gz/.z... It is an AI Agent Skill for Claude Code / OpenClaw, with 265 downloads so far.
How do I install paper-review?
Run "/install paper-review" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is paper-review free?
Yes, paper-review is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does paper-review support?
paper-review is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created paper-review?
It is built and maintained by helloml0326 (@helloml0326); the current version is v1.0.0.
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