Gabriel Martín Moran

What an agent can do with the mind corpus

GabrielMartinMoran/mind: Persistent local memory for AI coding agents. Preserve decisions and project context across sessions, compaction, and tools

• Look up how mind implements agent-memory, ai-agents, antigravity, with answers cited to file and line.
• Reuse a worked example: the commit “OmniMemEval RAG A/B and GPT-6 Luna low evaluation” (8 files · TypeScript, Python).
• Answer from mind's real TypeScript source instead of memory (AI, prompts and agents).

• Where does mind handle “OmniMemEval RAG A/B and GPT-6 Luna low evaluation”?
• How does mind implement agent-memory?
• What does benchmarks do in mind?

Search the GitHub repository GabrielMartinMoran/mind with XERJ (https://hub.xerj.org/corpus/gabrielmartinmoran--mind).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/GabrielMartinMoran/mind mind && git -C mind checkout b1e41202f42fd3195dabaa2c726523c2eb22e800
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./mind --url http://127.0.0.1:9200 --prefix mind --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: MIT. Keep the copyright notice and credit the authors.

corpus gabrielmartinmoran--mind · AI, prompts and agents
Related corpora: xerj-blogposts, faah, jayzeng/agentmemory, kanghyunsoon/duo
AI search and retrieval with XERJ · Case study: reference coding for agents