1,000 to 10,000 synthetic records designed for fine-tuning Large Language Models in tool-calling and agentic orchestration tasks. Created by bellfire and updated in February 2026, it provides bilingual support for English and Indonesian within the OpenClaw ecosystem.
Use Cases
- Fine-tuning models for multi-step tool calling using the reasoning chain features
- Improving agentic orchestration by training on conversational context examples
- Developing Indonesian-language AI agents using the bilingual tool-calling records
Strengths
- 1,000 to 10,000 synthetic records
- Optimized for Qwen 2.5 14B architecture
- Bilingual support for English and Indonesian
Limitations
- Synthetic data generation may result in repetitive patterns compared to human-authored logs
- Small sample size of under 10,000 records
- Narrow focus on OpenClaw ecosystem tools
Provenance
- Source
- bellfire
- Collection Method
- synthetic
- Freshness
- Updated February 2026