Awesome AI Memory | LLM Memory | A curated knowledge base on AI memory for LLMs and agents, covering long-term memory, reasoning, retrieval, and memory-native system design. Awesome-AI-Memory 是一个 集中式、持续更新的 AI 记忆知识库，系统性整理了与 大模型记忆（LLM Memory）与智能体记忆（Agent Memory） 相关的前沿研究、工程框架、系统设计、评测基准与真实应用实践。
Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add IAAR-Shanghai/Awesome-AI-Memory
Maintenance
active
1mo since push
Risk
Safe to try
Quality score needs review
GitHub quality
978
84/100 quality · 83/100 trust
Coverage tags
Review notes
Quality score needs review
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Safe to tryInstall readiness, security metadata, maintenance, and adoption risk.
Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
978 GitHub stars
Repo activity
978 stars, 92 forks
Maintenance
1mo since push
License
Apache-2.0
Install
npx skills add IAAR-Shanghai/Awesome-AI-Memory
Install safety
standard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add IAAR-Shanghai/Awesome-AI-MemoryDo not use when
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Agent safety v2
Good audit and safety signals with no high-risk permission hints in public metadata.
Review the audit page, then allow agent install in a sandboxed workflow.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Install targets
Copy the registry command or an agent-specific install prompt for Codex, Claude Code, and Cursor.
Use the registry command when your workflow supports the OpenAgentSkill installer.
$ npx skills add IAAR-Shanghai/Awesome-AI-MemoryAgent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Resolve JSON
/api/agent/resolve?task=Use%20Awesome%20AI%20Memory%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20Awesome%20AI%20Memory%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/iaar-shanghai-awesome-ai-memory/install
Agent should check
Copy prompt
Task: Use Awesome AI Memory in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Awesome%20AI%20Memory%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/iaar-shanghai-awesome-ai-memory/install
Install command: npx skills add IAAR-Shanghai/Awesome-AI-Memory
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/iaar-shanghai-awesome-ai-memory/install
LLM text format
/api/skills/iaar-shanghai-awesome-ai-memory/install?format=text
Find alternatives
/api/skills/search?q=Awesome%20AI%20Memory&limit=3
Agent prompt
Use Awesome AI Memory for this task. Review https://www.openagentskill.com/api/skills/iaar-shanghai-awesome-ai-memory/install, then install with: npx skills add IAAR-Shanghai/Awesome-AI-MemoryRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/iaar-shanghai-awesome-ai-memory
LLM text
/api/registry/manifest/iaar-shanghai-awesome-ai-memory?format=text
Install alias
/api/registry/install/iaar-shanghai-awesome-ai-memory
Recommend
/api/registry/recommend?task=Use%20Awesome%20AI%20Memory%20in%20an%20agent%20workflow&limit=3
Agent fit
RAG and knowledge
Use-case tags
Platforms
Python, RAG, Claude Code
Audit report
Review install readiness, maintenance, trust, quality, and metadata warnings before adding this skill to an agent workflow.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
RAG and knowledge
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
Review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
INFO978 GitHub stars
Stars/forks activity
INFO978 stars, 92 forks; issue activity unavailable in current metadata
Recent maintenance
PASS1mo since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Stack fit
Ingest, retrieve, and cite
A stack for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
A stack for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
A stack for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
Similar skills in this category, ranked with the same readiness and quality signals.
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AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and more). Turn any folder of code, SQL schemas, R scripts, shell scripts, docs, papers, images, or videos into a queryable knowledge graph. App code + database schema + infrastructure in one graph.
Free and Open Source, Distributed, RESTful Search Engine
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
Awesome AI Memory | LLM Memory | A curated knowledge base on AI memory for LLMs and agents, covering long-term memory, reasoning, retrieval, and memory-native system design. Awesome-AI-Memory 是一个 集中式、持续更新的 AI 记忆知识库，系统性整理了与 大模型记忆（LLM Memory）与智能体记忆（Agent Memory） 相关的前沿研究、工程框架、系统设计、评测基准与真实应用实践。
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Frameworks & Tools
Decision snapshot
978 GitHub stars
Audit snapshot
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the audit before production use.
Growth loop
Scenario-led draft for Awesome AI Memory, ready for a manual X post.
The useful research skills are not search wrappers. They help agents keep sources attached. Awesome AI Memory helps agents turn docs, data, or knowledge bases into grounded work. 978 stars https://www.openagentskill.com/skills/iaar-shanghai-awesome-ai-memory?ref=x #AIAgents
Listing + install path for Awesome AI Memory: https://www.openagentskill.com/skills/iaar-shanghai-awesome-ai-memory?ref=x Install: npx skills add IAAR-Shanghai/Awesome-AI-Memory
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This community indexed listing is attributed to IAAR-Shanghai but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/iaar-shanghai-awesome-ai-memory)
[](https://www.openagentskill.com/skills/iaar-shanghai-awesome-ai-memory)
[](https://www.openagentskill.com/skills/iaar-shanghai-awesome-ai-memory/audit)
[](https://www.openagentskill.com/skills/iaar-shanghai-awesome-ai-memory)IAAR-Shanghai
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