ybeven / 4D-ARE
Build LLM agents that explain why, not just what. Attribution-driven agent requirements engineering framework. Based on the 4D-ARE Paper - https://arxiv.org/abs/2601.04556
Why this job: matched by what the repo talks about: agent, framework, llm, engineer
What it does
- D_R (Results). Observable outcomes - display only
- D_P (Process). Operational factors - interpret + recommend
- D_S (Support). Resource factors - suggest for review
- D_L (Long-term). Environmental factors - context only
Get started
pip install four-d-are- Maintenance
- Active
- Last commit 40 days ago
- Stars
- 182
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- 2
- Last 90 days
- Issues
- None
- No issues filed
- Pull requests
- 1 merged
- 0 waiting
- Releases
- None
- Never published
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
More: languages, topics and project record
Languages
- Python 100%
Topics
- agents
- causal-reasoning
- llm
- mcp
- prompt-engineering
- python
Project record
- JobAgent frameworks
- StatusListed
- Commits3
- Forks19
- Watching9
- Stars in 28 days0
- CreatedJan 9, 2026
- First seen by usNov 7, 2026
- CheckedNov 7, 2026