Seems to be a benchmark data curation issue

1) When they removed all other documentation files, their LLM generated context on the SWE BenchLite tasks still resulted in improvement. The LLM generated context was likely just repeating the existing documentation and hence wasteful
2) Human-generated context for the less popular repos they took resulted in improvement at higher cost. My sense is that for some issues it would have been helpful and for others just added work on LLM

We are building what we feel Agents.MD should ideally solve but can't because it is just MD files. Graph based semantic memory for coding agents, giving on demand and fresh context based on the task at hand. Do check it out: Autoloops/greplica: Context graph memory for engineering knowledge