Virtual Reading Group

Orchestrate a multi-agent virtual academic reading group. Use when reading multiple papers, generating expert discussion notes, cross-examining positions acr...

This skill appears internally consistent and does not ask for secrets or installs. Before running it, confirm: (1) the list of papers you provide — the agents will read any files/paths you give them, so do not point the skill at sensitive or private documents you don't want processed; (2) whether you allow network lookups — if you provide only local PDFs you avoid external fetching, but allowing 'web lookup' may cause the agent to fetch content from the internet; (3) that you are comfortable with verbatim quoting — templates require direct passages and granular citations which can reproduce copyrighted text. Also note the skill recommends specific internal models (opus/sonnet) — using them may affect cost/usage if applicable. If you want additional assurance, run the skill on a small, non-sensitive sample first and check outputs.

Type: OpenClaw Skill Name: virtual-reading-group Version: 1.1.0 The skill orchestrates a multi-agent academic reading group, requiring extensive file system access (reading user-provided papers, writing intermediate and final markdown reports to a specified output directory). This capability, while high-risk, is explicitly stated and essential for the skill's purpose. All instructions to the AI agents across `SKILL.md`, `references/workflow.md`, `references/default-personas.md`, and `references/paper-notes-template.md` are focused on guiding task execution, maintaining academic integrity (e.g., strict citation rules, anti-fabrication instructions), and adopting specific personas. There is no evidence of intentional harmful behavior such as data exfiltration, unauthorized command execution, persistence mechanisms, or obfuscation. The prompt instructions are designed to enhance the agent's performance and integrity, not to subvert it.