virtual-reading-groupOrchestrate a multi-agent virtual academic reading group. Use when reading multiple papers, generating expert discussion notes, cross-examining positions acr...
Install via ClawdBot CLI:
clawdbot install IsonaEi/virtual-reading-groupGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 1, 2026
Research teams analyzing 5-10 recent papers on a specific topic, such as climate change impacts, to generate integrated summaries and identify gaps for grant proposals or literature reviews.
Technology companies evaluating 3-5 competitor patents or technical papers to synthesize insights for product development strategies and innovation roadmaps.
Government agencies or NGOs reviewing 10-15 studies on public health interventions to create evidence-based policy briefs with traceable citations and expert consensus points.
Drug development teams analyzing 8-12 clinical trial papers to cross-examine findings, synthesize safety profiles, and prepare regulatory submission documents.
Law firms examining 4-6 academic articles or precedent studies to build arguments, challenge opposing interpretations, and draft integrated legal memos.
Offer tiered monthly plans based on paper volume (e.g., up to 10 papers for startups, 50 for enterprises) with features like custom personas and priority support, targeting research institutions and corporations.
Bundle the skill with expert-led workshops or analysis sessions for clients in academia or industry, providing tailored reports and follow-up discussions as a premium offering.
Provide a free tier for up to 3 papers to attract individual researchers, then charge for API calls or advanced features like multi-language support and bulk processing for developers and large teams.
💬 Integration Tip
Ensure sub-agent spawning mechanisms support parallel execution and file I/O for output directories, and validate paper formats (PDF/text) upfront to avoid workflow interruptions.
Scored May 30, 2026
Meta-skill for AI agent self-improvement. Analyzes runtime logs to detect error patterns, regressions, and inefficiencies, then generates structured improvem...
Stop waiting for prompts. Keep working.
Turn OpenClaw into a learning-loop agent with seeded workspace rules, skill promotion, reflective memory, and proactive maintenance.
Meta-agent skill for orchestrating complex tasks through autonomous sub-agents. Decomposes macro tasks into subtasks, spawns specialized sub-agents with dynamically generated SKILL.md files, coordinates file-based communication, consolidates results, and dissolves agents upon completion. MANDATORY TRIGGERS: orchestrate, multi-agent, decompose task, spawn agents, sub-agents, parallel agents, agent coordination, task breakdown, meta-agent, agent factory, delegate tasks
Complete toolkit for creating autonomous AI agents and managing Discord channels for OpenClaw. Use when setting up multi-agent systems, creating new agents, or managing Discord channel organization.
Billions decentralized identity for agents. Link agents to human identities using Billions ERC-8004 and Attestation Registries. Verify and generate authentic...