ctxvault
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- AlicenseAqualityBmaintenanceLocal memory for AI agents over plain Markdown files: hybrid vector + BM25 recall (RRF), one isolated memory per agent directory, fully offline with no LLM in the loop. Tools: cogvault_recall and cogvault_record.242 PyPI1MIT
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TDQS
Scored across 17 tools
Tools split cleanly into three domains (document vaults, skill vaults, episodic memory) and the descriptions cross-reference each other explicitly, e.g. invalidate_episode points to supersede_episode and revise_episode distinguishes 'world changed' from 'said better'. The only residual overlap is between query/query_episodes/list_docs, which is mitigated but not eliminated by the doc-vs-episode framing.
Fourteen of seventeen tools follow a clean verb_noun snake_case pattern (list_vaults, write_doc, read_skill, supersede_episode, list_entities). The outliers — query, episode_history, warmup_status — are readable but break the verb-first convention.
Seventeen tools is slightly heavy but justified by covering three distinct storage modes (documents, skills, temporal episodes) plus warmup and entity enumeration. No tool looks redundant enough to remove; episode lifecycle tools each handle a genuinely different case.
Episodic memory is exceptionally complete (write, query, confirm, invalidate, supersede, revise, dispute, history), but the document and skill surfaces are write/list/read only — no update, delete, or move for docs or skills, and no create_vault despite list_vaults implying vault management. These gaps will cause dead ends for maintenance workflows.