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
RE-Framework
unknowbug/RE-Framework
RE-Framework is a tool for DeepSeek Harness. Modular engineering methodology framework for AI agents — reverse engineering & software development (core + re-binary / re-code / swe modules).
- Stars
- 7
- Forks
- 2
- Issues
- 0
- Update
- 42 days
REVIEW SCORECARD
Review Scorecard
6.7/10Average
License compliance6.0
Engineering quality5.8
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
7.4/10Consider
Well-structured modular agent methodology framework with tests and self-checks, but PowerShell-only install and unverifi
Code quality8
README documents a structured dsh/ tree with tests (test_manifest.py, check_plugin_schema.mjs), a selfcheck.ps1 four-stage validation, and a single-source-of-truth skills layout.
Security6
Install runs a PowerShell script (pwsh dsh/scripts/install.ps1) that writes to the user-level ~/.dsh/skills directory, but no secrets, permissions, or download sources are shown, so risk cannot be fully assessed.
Utility8
Targets a real pain point by packaging reverse-engineering and software-development workflows into 17 loadable skills plus 3 model tools for DSH agents.
Maintenance8
Actively maintained with v2.3 dated 2026-08-21, a documented version history, and a recent DSH-only host migration, though the repo has only 7 stars.
Documentation7
README provides install commands, an architecture tree, a 17-skill table, and an Anchorlaw relationship table, but is written in Chinese and assumes familiarity with DSH and Anchorlaw concepts.
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
pwsh dsh/scripts/install.ps1This 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
VALIDATION LADDER
Validation progress
01Store discoveryPassed
02ClassificationPassed
03Structure checkPending
04Sandbox validationPending
FAQ
Frequently Asked Questions
What is RE-Framework used for?
Modular engineering methodology framework for AI agents — reverse engineering & software development (core + re-binary / re-code / swe modules).
How popular is RE-Framework?
RE-Framework has 7 stars and 2 forks on GitHub, last updated 2026-08-22.
Is RE-Framework compatible with DeepSeek Harness?
RE-Framework 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:code-analysis、developer-tools、engineering-workflow、methodology、multi-agent、subagents。
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MemOS
MemTensor
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Structure check pending
agentagentic-aiaiai-agents
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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
agentagent-memoryai-agentsclaude-code
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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