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Install in OpenClaw
/install paper-engineering-assistant
Description
基于“框架层-总结层-正文层”三层架构的自动化论文写作与文献管理助手。严格按照用户指定的目录(`workspace/毕业论文`)组织所有文件。
Usage Guidance
This skill's documentation promises substantial automation (download PDFs, parse text, summarize, and automatic bidirectional sync) but the provided code is a small, mostly placeholder script that only creates directories, lists project structure, and contains a stub for updating summaries. Before installing or using it: 1) Back up any real thesis/work directories — the skill explicitly overwrites body files. 2) Ask the author for the missing implementations: what libraries/tools will be used for PDF parsing, what network endpoints will be contacted, and how synchronization is triggered (file watcher, webhooks, or manual). 3) If you need network access disabled, run the skill in an isolated/test folder or restrict its network privileges. 4) Prefer to run the included agent.py in a sandbox to confirm behavior and to obtain a complete implementation (download/parsing/sync code) before giving it access to important files. If the author cannot justify where downloads will come from or cannot provide the actual parsing/sync code, treat the skill as incomplete and avoid using it on important data.
Capability Analysis
Type: OpenClaw Skill
Name: paper-engineering-assistant
Version: 1.0.1
The skill requests broad permissions, including 'Filesystem read/write' and 'network access', as declared in SKILL.md. While these permissions are plausible for an academic writing assistant, the instructions in SKILL.md for the agent to parse arbitrary reference files (e.g., PDFs) and perform network downloads based on user-provided keywords introduce significant vulnerability risks. These capabilities could be exploited through parser vulnerabilities or by tricking the agent into downloading/processing malicious content or performing SSRF, even though the provided `agent.py` code does not explicitly implement these risky parsing/downloading functions, nor does it show clear malicious intent.
Capability Assessment
Purpose & Capability
The SKILL.md describes a full-featured pipeline (PDF download/parse, literature search, automated summarization, full bidirectional synchronization). The shipped agent.py only implements directory creation, a simple project-structure reporter, and a placeholder summary-update routine; it does not perform network calls, PDF parsing, summarization, or file-watching. Also the top-level description (Chinese: organize under workspace/毕业论文) conflicts with SKILL.md/agent.py default './PaperProject/'. This mismatch between claimed capability and actual footprint is inconsistent.
Instruction Scope
Runtime instructions request filesystem read/write across a project tree and network access for literature search and downloads; they also state that body files may be overwritten and that synchronization must run after each modification. The code, however, provides no implementation for downloads, parsing, or an automatic synchronization/watch mechanism, so the instructions grant broad behaviors that are not constrained or implemented. Overwrite behavior is explicit in the docs and could be destructive if run in a real project directory.
Install Mechanism
No install spec is provided and no external packages are fetched; risk from install mechanism is low. The skill is instruction-plus-a-small-agent script; nothing is downloaded or extracted during install.
Credentials
The skill declares network access and filesystem read/write in its runtime instructions but requires no environment variables or credentials. That is plausible for generic literature searches, but the SKILL.md does not declare which external services/endpoints will be contacted or whether credentials (institutional access, library proxies) are needed. The lack of declared secrets is not an immediate red flag, but network access plus unspecified endpoints increases ambiguity.
Persistence & Privilege
The skill is not marked 'always: true' and does not request special system-wide privileges. It exposes async functions (initialize_project, sync_on_body_change) that a gateway could call, but that is consistent with normal skill operation. Autonomous invocation is allowed by default (platform default) — combine that with network/filesystem access if you want to limit risk.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install paper-engineering-assistant - After installation, invoke the skill by name or use
/paper-engineering-assistant - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
- Initial metadata file (_meta.json) added for skill packaging and cataloging.
- No changes to core functionality or user-facing features in this version.
- All previous logic and workflows remain unchanged.
v1.0.0
initinit
Metadata
Frequently Asked Questions
What is Paper Engineering Assistant?
基于“框架层-总结层-正文层”三层架构的自动化论文写作与文献管理助手。严格按照用户指定的目录(`workspace/毕业论文`)组织所有文件。 It is an AI Agent Skill for Claude Code / OpenClaw, with 499 downloads so far.
How do I install Paper Engineering Assistant?
Run "/install paper-engineering-assistant" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Paper Engineering Assistant free?
Yes, Paper Engineering Assistant is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Paper Engineering Assistant support?
Paper Engineering Assistant is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Paper Engineering Assistant?
It is built and maintained by 陈宽同学 (@mrchenkuan); the current version is v1.0.1.
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