我问claude关于技术选型，结果让我意外。

[HuangKaibo2017]

这是我的问题：
by the 5 gaps (Passive per-tool capture, Zero-model operation, Git-native / human-readable, Multi-scope isolation, Importance scoring / decay), if i want to customize existing solutions, what whould be the best for minium effort and easy testing. i thought it would be easy to keep all memory as text file (md, json, toml). i know there are some options:

1. openclaw (version 2026.3.11) https://github.com/tobi/qmd, lancerdb
2. https://github.com/memovai/memov
3. https://github.com/opendatalab/MinerU
4. https://github.com/VectifyAI/PageIndex
5. https://github.com/volcengine/OpenViking
6. https://github.com/MemoriLabs/Memori
7. https://github.com/steveyegge/beads
8. https://github.com/EverMind-AI/EverMemOS

claude给的关键结论。

Recommended Minimum-Effort Stack
MemoV → Gaps 1, 2, 3 (passive capture, no model, git-native)
Beads → Gaps 4, 5 (scope isolation, memory decay/compaction)
OpenClaw → Keep as orchestration shell only
OpenViking → Skip
EverMemOS → Skip (Docker + MongoDB + Elasticsearch + Milvus + Redis — far from minimum effort)