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-mnemon
omdsh-dev/dsh-mnemon
dsh-mnemon is a tool for DeepSeek Harness. Composable, view-based memory for DeepSeek Harness. Pluggable sources and strategies, with three-tier memory out of the box.
- Stars
- 444
- Forks
- 37
- Issues
- 4
- Update
- today
REVIEW SCORECARD
Review Scorecard
8.4/10Good
License compliance9.0
Engineering quality7.9
Content completeness8.0
Repository scale7.0
Maintenance activity9.0
✓ No risk detected · Automated scan results are for reference only, not an official endorsement
AI DEEP REVIEW
Worth AI Review
8.0/10Recommended
A well-documented, actively maintained three-tier memory plugin for DSH that solves real cross-session context pain poin
Code quality8
README describes a structured Source/Strategy/Core architecture with immutable Views, a tested default Starter plugin combination, and explicit compatibility baselines, though no CI or test suite details are shown.
Security7
Install is a standard npm package add with no download-and-execute scripts visible, but the README notes Mnemon Native requires a separately installed `mnemon` CLI binary and third-party backend services whose provenance is not described.
Utility9
Addresses a common agent pain point by splitting runtime context, searchable documents, and durable long-term memory into three tiers with shared Sidebar, conversation tools, and headless access.
Maintenance8
Last updated 2026-08-26 with an active release line (v0.5.4 demo, v0.4 upgrade path) and a documented DSH 0.1.5-rc.1 baseline, indicating ongoing development.
Documentation8
README links to getting-started, UI, architecture, compatibility, operations, and workflow docs in English and Chinese, with install commands and upgrade checklists, though some linked content is not shown here.
Generated by AI after reading the project README — a decision aid, not an endorsement. Neutral scores are given when information is limited.
PROJECT READMEREADMEExpandCollapse
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Open repositoryINSTALL REFERENCE
Install reference
dsh plugin --profile web add dsh-mnemonThis command was extracted from an explicit README install reference and is display-only; the DSH host will not execute it automatically.
PROJECT TOPICS
Project topics
agent-memorycontext-managementcross-session-memorydeepseek-harnessdocument-searchdsh-better-sidebardsh-mnemondsh-pluginllm-memorylocal-firstlong-term-memorymemory-orchestrationmemory-providermulti-agent-memorypersistent-memorypluggable-memoryproject-memoryruntime-memorysemantic-recallshared-agent-memory
VALIDATION LADDER
Validation progress
01Store discoveryPassed
02ClassificationPassed
03Structure checkPending
04Sandbox validationPending
FAQ
Frequently Asked Questions
What is dsh-mnemon used for?
Composable, view-based memory for DeepSeek Harness. Pluggable sources and strategies, with three-tier memory out of the box.
How popular is dsh-mnemon?
dsh-mnemon has 444 stars and 37 forks on GitHub, last updated 2026-10-02.
What license does dsh-mnemon use?
dsh-mnemon is distributed under the MIT license.
Is dsh-mnemon compatible with DeepSeek Harness?
dsh-mnemon 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、context-management、cross-session-memory、document-search、llm-memory、long-term-memory、memory-orchestration、memory-provider、multi-agent-memory、persistent-memory、pluggable-memory、project-documents、project-memory、runtime-memory、shared-agent-memory、working-memory。
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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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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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