Academic Paper Summarizer

Academic paper summarization with dynamic SOP selection based on paper topic classification. Supports method, dataset, multimodal, and other paper types with...

This skill appears coherent and low-risk, but review a few things before installing: 1) Confirm you are comfortable that summaries and the raw prompts will be saved to local disk (research/{domain}/...) — if you process confidential papers, those files may contain sensitive text. 2) Inspect templates/sop_templates.ts (the included system prompt) to ensure the behavior and output format (strict JSON with embedded Markdown/LaTeX) match how you plan to consume results. 3) Note documentation inconsistencies (SKILL.md references different file paths; length requirements vary across files). These are not security issues but could cause runtime mismatches. 4) Because the skill enforces long, detailed outputs, check resource/time expectations when batch-processing many papers. If you want extra assurance, run the skill in a sandboxed environment, examine the files it writes, and confirm no unexpected network activity occurs during use.

Type: OpenClaw Skill Name: paper-summarize-academic Version: 1.0.1 The OpenClaw skill 'paper-summarize-academic' is designed for academic paper summarization, saving structured output and prompts to local files. All instructions to the AI agent in `SKILL.md` and `templates/sop_templates.ts` are focused on the summarization task, defining the agent's persona, output format, and quality standards. File write operations are explicitly stated and necessary for the skill's function, and `USAGE_EXAMPLE.md` shows filename sanitization (`safeTitle = title.replace(/[^a-zA-Z0-9]/g, '_');`), which is a good security practice. There is no evidence of malicious intent, data exfiltration, unauthorized execution, or prompt injection designed to subvert the agent for harmful purposes.