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-expert-mode
Asher-2000/dsh-expert-mode
dsh-expert-mode is a tool for DeepSeek Harness. DSH (DeepSeek Harness) expert mode agent preset — Chief Coordinator + 16 domain expert sub-agents Expert-mode preset for DeepSeek Harness
- Stars
- 8
- Forks
- 0
- Issues
- 1
- Update
- 38 days
REVIEW SCORECARD
Review Scorecard
7.5/10Average
License compliance9.0
Engineering quality5.4
Content completeness7.0
Repository scale7.0
Maintenance activity8.0
✓ No risk detected · Automated scan results are for reference only, not an official endorsement
AI DEEP REVIEW
Worth AI Review
7.0/10Consider
A feature-rich multi-agent expert preset with strong docs, but limited visible engineering evidence and no security deta
Code quality6
README references bus.py and taskboard.py with a state machine and dependency DAG, but no tests, CI config, or repo structure are shown, so rigor cannot be verified.
Security6
No download-and-execute patterns, secrets, or permission details appear in the provided info; the install path is a standard dsh plugin add, so a neutral score is given.
Utility8
Solves a real pain point by auto-routing tasks to 17 domain experts with quality gates, taskboard scheduling, and fault recovery, removing manual prompt/config setup.
Maintenance8
Last updated 2026-08-26, not archived, MIT licensed, with npm publishing and release badges indicating ongoing activity.
Documentation7
README is bilingual with install commands, expert tables, feature descriptions, and screenshots, though the install section is truncated mid-sentence.
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 github:Asher-2000/dsh-expert-modeThis command passed the install-plan safety checks and can be executed by the DSH host. Validation is not a security audit or official endorsement.
PROJECT TOPICS
Project topics
VALIDATION LADDER
Validation progress
01Store discoveryPassed
02ClassificationPassed
03Structure checkPending
04Sandbox validationPending
FAQ
Frequently Asked Questions
What is dsh-expert-mode used for?
DSH (DeepSeek Harness) expert mode agent preset — Chief Coordinator + 16 domain expert sub-agents Expert-mode preset for DeepSeek Harness
How popular is dsh-expert-mode?
dsh-expert-mode has 8 stars and 0 forks on GitHub, last updated 2026-08-26.
What license does dsh-expert-mode use?
dsh-expert-mode is distributed under the MIT license.
Is dsh-expert-mode compatible with DeepSeek Harness?
dsh-expert-mode 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:multi-agent、subagent。
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MemTensor
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harness support.
Structure check pending
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harnessrouter
HarnessRouter
HarnessRouter Community Edition: the self-hosted, Apache-2.0 edition of the unified interface for agent harnesses. Run Codex, Claude Code, Hermes, PI, DSH, and more through one API, with sessions, streaming, files, cancellation, and failure handling. Implements the Unified Harness Protocol (UHP), an open standard. Your keys, your infrastructure.
Structure check pending
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A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex, DSH), backed by Markdown and Milvus.
Structure check pending
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Tianshu-harness
huiliyi37
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
ai-agentcoding-agentcontext-managementdeepseek
Agents & sessionsPlugin
graph-memory
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
claude-codecodexdeepseekdeepseek-harness