What does NexFlow-AI-Framework do?
Orchestrate multi-agent AI workflows using open-source neural networks for internal support and structured data extraction in enterprise environments.
Orchestrate multi-agent AI workflows using open-source neural networks for internal support and structured data extraction in enterprise environments.
NexFlow-AI-Framework is a Claude Code agent skill that orchestrate multi-agent AI workflows using open-source neural networks for internal support and structured data extraction in enterprise environments.
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Orchestrate multi-agent AI workflows using open-source neural networks for internal support and structured data extraction in enterprise environments.
Agent skill repository discovered by 10x-chat research.
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USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
Evidence-first current-state research workflow for ECC. Use when the user wants fresh facts, comparisons, enrichment, or a recommendation built from current public evidence and any supplied local context.