oneal2000 / SR-Agents
SRA-Bench and SR-Agents: a benchmark and toolkit for skill-retrieval-augmented LLM agents.
Why this job: says: benchmark; topics: benchmark
What it does
Modern LLM agents are no longer just text generators. They increasingly rely on external skills: reusable capability packages that may include natural-language instructions, tool-use procedures, executable code, and auxiliary resources.
Get started
pip install -e .
# or: uv sync- Maintenance
- Active
- Last commit 4 months ago
- Stars
- 110
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v1.0.0
- Released 6 months ago
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- 0
- Last 90 days
- Issues
- 0% closed
- 1 still open
- Pull requests
- 0 merged
- 0 waiting
- Releases
- 1
- 1 in the last year
- No contributing guide
- No security policy
- No code of conduct
More: languages, topics and project record
Languages
- Python 100%
Topics
- agent-memory
- agent-skills
- agentic-ai
- benchmark
- llm-based-agents
- rag
- retrieval-augmented-generation
- skill-learning
- skill-retrieval
- skill-retrieval-augmentation
- tool-use
Project record
- JobEvals and observability
- StatusListed
- Commits25
- Forks14
- Watching1
- Stars in 28 days+2
- CreatedApr 16, 2026
- First seen by usNov 7, 2026
- CheckedNov 7, 2026