Agents & sessionsSkill
EverOS
EverMind-AI
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
Structure check pending
agent-memoryagentic-aiaichats
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Agents & sessionsPlugin
dsh-memory
aqsk-BLG/dsh-memory
dsh-memory is a tool for DeepSeek Harness. Layered file memory for DeepSeek Harness — workspace-scoped USER/MEMORY notes, background consolidation, hybrid session recall. npm: dsh-file-memory
- Stars
- 3
- Forks
- 0
- Issues
- 0
- Update
- 43 days
REVIEW SCORECARD
Review Scorecard
6.8/10Average
License compliance6.0
Engineering quality5.4
Content completeness8.0
Repository scale7.0
Maintenance activity8.0
✓ No risk detected · Automated scan results are for reference only, not an official endorsement
PROJECT READMEREADMEExpandCollapse
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Open repositoryPROJECT TOPICS
Project topics
VALIDATION LADDER
Validation progress
01Store discoveryPassed
02ClassificationPassed
03Structure checkPending
04Sandbox validationPending
FAQ
Frequently Asked Questions
What is dsh-memory used for?
Layered file memory for DeepSeek Harness — workspace-scoped USER/MEMORY notes, background consolidation, hybrid session recall. npm: dsh-file-memory
How popular is dsh-memory?
dsh-memory has 3 stars and 0 forks on GitHub, last updated 2026-08-19.
Is dsh-memory compatible with DeepSeek Harness?
dsh-memory is listed in the DSH Universe directory as a tool for DeepSeek Harness. This plugin is listed in the DSH Universe directory and covered by its validation pipeline.
CLASSIFICATION EVIDENCE
Classification evidence
Project typePlugin
Feature categoryAgents & sessions
Rule confidenceHigh
The system checks GitHub Topics against the site taxonomy and keyword rules. Current matches:agent-memory、memory。
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Structure check pending
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Structure check pending
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Structure check pending
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Tianshu is a terminal coding agent runtime built on the harness project (Tui X Gui), with prefix-cache engineering optimization for DeepSeek V4 (measured steady-state hit rate of 97–99% in long sessions) and deep adaptation. It breaks out of the traditional AI coding assistant's limit of treating the LLM merely as a tool, and is built on a cognitive virtual machine (CVM), a self-awareness layer and Stigmergy self-decaying memory, making the AI a development partner with independent judgment and cognitive safeguards.
Structure check pending
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adoresever
Deepseek Harness, Openclaw knowledge graph memory plugin. Invited to present at Tsinghua University seminar in April 2026. Knowledge Graph + Memory；Knowledge Graph Context Engine for OpenClaw — extracts structured triples from conversations, compresses context 75%, enables cross-session experience reuse
Structure check pending
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