sibyl-research-system
by Sibyl-Research-Team
Autonomous Claude Code research agents for experiment execution and paper generation
Summary
Orchestrates fully autonomous research workflows built natively on Claude Code, running agents that design, run, and analyze experiments. Agents self-evolve and self-heal by iterating on experiments, scheduling GPU jobs, and generating draft papers. Distinctive features include end-to-end experiment execution, multi-agent delegation, and automated paper-generation pipelines. This approach leverages semantic-capability matching to coordinate diverse agent capabilities across tasks semantic-capability-matching-pattern.
Why It Matters
When to Use
Research teams exploring autonomous, multi-agent experiment pipelines who want self-evolving agents and reproducible experiment artifacts. This fits well with organizations adopting hierarchical coordination for large-scale experiments Hierarchical Multi-Agent Pattern, and with teams refining internal reasoning and decision processes using chain-of-thought strategies Chain of Thought Pattern.
Applications
- Automating experiment design, execution, and result analysis across GPU clusters
- Iterating on model experiments with agents that propose, run, and refine trials
- Generating reproducible research artifacts and draft papers from agent workflows