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
engramory
tinqiao-oss/engramory
engramory is a tool for DeepSeek Harness. A portable memory protocol for AI agents — load it as standing rules; a curation discipline + reference spec + optional cap hook.
- Stars
- 174
- Forks
- 11
- Issues
- 2
- Update
- 44 days
REVIEW SCORECARD
Review Scorecard
7.9/10Average
License compliance9.0
Engineering quality7.5
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
7.6/10Consider
A well-documented, actively maintained markdown memory protocol with honest limitations, but experimental and lacking a
Code quality8
README shows a CI badge, a Python 3.9+ validator tool (tools/engramory_doctor.py), and a PreToolUse hook, indicating real engineering structure, though no test details are visible.
Security7
No download-and-execute or plaintext-secret patterns appear in the README, and the store is git-ignored, but the hook's permission scope is only partially described, so risk is moderate.
Utility8
It targets a real, common pain point — bounded, non-rotting agent memory — with a concrete index cap and curation discipline, though it explicitly admits best-effort enforcement.
Maintenance8
Last updated 2026-08-20, version 0.11.0, not archived, with CI badge and active issue references, indicating ongoing development.
Documentation7
README is thorough and self-aware, but the install command is listed as unknown and setup is deferred to AGENT-SETUP.md, leaving a gap for human users.
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 repositoryPROJECT TOPICS
Project topics
VALIDATION LADDER
Validation progress
01Store discoveryPassed
02ClassificationPassed
03Structure checkPending
04Sandbox validationPending
FAQ
Frequently Asked Questions
What is engramory used for?
A portable memory protocol for AI agents — load it as standing rules; a curation discipline + reference spec + optional cap hook.
How popular is engramory?
engramory has 174 stars and 11 forks on GitHub, last updated 2026-08-20.
What license does engramory use?
engramory is distributed under the MIT license.
Is engramory compatible with DeepSeek Harness?
engramory 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、claude-code、llm-memory、long-term-memory、markdown、memory、prompt-engineering。
Agents & sessionsSkill
MemOS
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
agentagentic-aiaiai-agents
Agents & sessionsPlugin
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
agent-apiagent-frameworkagent-harnessai-agents
Agents & sessionsSkill
memsearch
zilliztech
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
Agents & sessionsPlugin
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