How GLM-5-Turbo Turns an AI Research Lab into a 24‑Hour Autonomous Writer

01 This Lobster Model Is Different

GLM-5-Turbo, marketed as the world’s first "lobster model", is fine‑tuned for multi‑step tool‑calling tasks and evaluated with the ZClawBench benchmark, where it surpasses mainstream models on several key metrics.

Lab Members and Required Skills

The AI research Lab consists of five specialized agents, each driven by a distinct skill:

Topic Agent : brainstorming-research-ideas, creative-thinking-for-research, autoglm-websearch Literature Agent : autoglm-websearch, start-my-day Outline Agent : creative-thinking-for-research, ml-paper-writing Writing Agent : ml-paper-writing Submission Agent : ml-paper-writing (configured for AAAI/NeurIPS/ICLR LaTeX templates)

All skills are installed via one‑click commands; the installation process is described as seamless and error‑free.

Prompt Template for the Topic Agent

你是【选题虾】，AI科研Lab的“大脑”，只负责确定综述的最终选题、核心论点和目标受众，禁止越权做其他角色的任务。【你的核心职责】负责确定综述的最终选题、核心论点（Thesis）和目标受众。需要评估指定Topic领域的当前研究热点、趋势空白，并明确综述的创新性视角（例如：从技术演进、架构对比或应用挑战等角度）。最终输出一份清晰的研究定位报告。【你的技能规则】....

02 One Hour of Crazy Automation

Providing the simple prompt Top=OpenClaw triggers the five agents to work sequentially: the Literature Agent gathers 312 papers and filters 72 core ones, the Outline Agent creates a structured outline, the Writing Agent drafts the manuscript, and the Submission Agent formats the paper for AAAI.

The key innovation lies in the multi‑step reasoning of GLM-5-Turbo: it first generates five candidate topics, then evaluates feasibility with creative-thinking-for-research, and finally validates novelty via autoglm-websearch. This disciplined pipeline ensures the model truly understands “what makes a good research topic”.

After the full pipeline finishes, the entire paper—including PDF formatting—appears without any manual intervention, taking roughly 47 minutes. The author only needed to brew coffee while the AI Lab worked nonstop.

Cost and Practical Considerations

The GLM-5‑Turbo model is available through a token‑based API; a 1‑billion‑token monthly plan costs several thousand dollars, which the author notes is comparable to the compute needed for a single high‑quality survey paper.

Conclusion

The emergence of a dedicated "lobster model" like GLM-5‑Turbo dramatically raises the productivity of knowledge‑intensive work. By chaining specialized agents, researchers can automate the entire lifecycle of a survey paper—from idea generation to submission—without the typical interruptions or manual errors that plague traditional workflows.

For researchers overwhelmed by routine tasks, the combination of GLM-5‑Turbo and the AutoClaw platform offers a 24‑hour, non‑sleeping AI research Lab that reliably executes complex, multi‑step projects.