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Beta Agent Memory
by
1477009639zw-blip
· GitHub ↗
· v1.0.0
· MIT-0
131
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0
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1
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Install in OpenClaw
/install beta-agent-memory
Description
Long-term memory systems for AI agents. Implements vector memory, entity tracking, conversation summarization, and persistent context across sessions.
README (SKILL.md)
Agent Memory System
Give your AI agent persistent, long-term memory across conversations and sessions.
Memory Types Implemented
Episodic Memory
Stores episodes/events from conversations:
- Key facts extracted per conversation
- Decisions made and context
- User preferences and patterns
- "Remembering" past interactions
Semantic Memory
Structured knowledge storage:
- Entity definitions and relationships
- Facts about the world
- Domain knowledge base
- Learned procedures
Procedural Memory
Agent's own capabilities:
- Known skills and tools
- How to use different APIs
- Response patterns that worked
Architecture
User Input
↓
Short-term (current session context)
↓
Memory Retrieval → Top-k relevant memories (vector search)
↓
Context Injection → Combined prompt
↓
LLM Response
↓
Memory Storage → Extract new facts, update entities
Features
- Vector-based storage (ChromaDB or Pinecone)
- Entity extraction (spaCy NER)
- Conversation summarization (every N turns)
- Relevance scoring for retrieval
- Forgetting/summarization of old memories
Use Cases
- Personal AI assistant that remembers you
- Customer support agent with context
- Research agent with persistent knowledge
- Trading agent with market memory
- Personal CRM (remembering people and their context)
Technical Stack
- ChromaDB / Pinecone (vector store)
- spaCy (entity extraction)
- LangChain (memory abstractions)
- PostgreSQL (structured memory)
Pricing
| Type | Context Window | Price |
|---|---|---|
| Basic | 100K tokens | $100 |
| Pro | 1M tokens | $300 |
| Enterprise | Unlimited | $800 |
Built by Beta
Usage Guidance
This skill describes a memory system that would normally need service credentials (Pinecone API key, DB connection, etc.), installation steps, and explicit data-governance rules—but none are provided and the source/homepage is unknown. Before installing or enabling this skill, ask the publisher: Where is memory stored (local file/Chroma/Pinecone/Postgres)? What exact environment variables and permissions are required? How is sensitive data (PII) filtered, encrypted, and deleted? Who operates the storage (third party vs you)? Prefer a version that: lists required env vars, provides an install script or code repo, documents retention/consent policies, and supports a local-only mode (Chroma/embeddings stored locally) if you need privacy. If you handle sensitive data, avoid enabling this skill until provenance, storage, and credential details are provided or until you can review the implementation.
Capability Analysis
Type: OpenClaw Skill
Name: beta-agent-memory
Version: 1.0.0
The bundle contains only metadata and documentation (SKILL.md) describing a long-term memory system for AI agents. There is no executable code, suspicious commands, or prompt injection attempts present in the provided files (_meta.json and SKILL.md).
Capability Assessment
Purpose & Capability
The description and SKILL.md consistently describe a memory system using ChromaDB, Pinecone, spaCy, LangChain, and PostgreSQL. However, the registry metadata declares no required environment variables, no install steps, and no code—yet the described capabilities normally require API keys, database connections, and package installs. That discrepancy (features that need external services but no declared credentials or installs) is incoherent.
Instruction Scope
SKILL.md tells the agent to extract and persist episodic/semantic/procedural memories, run entity extraction, periodic summarization, and use vector search. It gives no concrete runtime commands but implicitly instructs the agent to collect and store user data across sessions. There is no guidance on what to store/omit, PII handling, retention, encryption, or where/how data is persisted—this is open-ended and could lead to inappropriate or unexpected data collection.
Install Mechanism
There is no install spec and no code files (instruction-only). That minimizes direct disk-write/install risk. However, the skill references Python libraries and external services that would normally require installation or service setup; the absence of an install mechanism contributes to the coherence concerns but is itself low-risk.
Credentials
The skill claims to use hosted services (Pinecone) and databases (PostgreSQL) which typically require API keys, tokens, or connection strings, yet requires.env is empty and no primary credential is declared. Requiring no credentials is disproportionate to the stated functionality and makes the specification incomplete or misleading.
Persistence & Privilege
always is false (good). The skill's purpose is persistent long-term memory; that inherently grants it privacy-sensitive persistence across sessions if implemented. The registry allows autonomous invocation (default), which combined with persistent memory behavior raises privacy concerns—especially given the lack of declared storage or governance—but autonomous invocation alone is not a disqualifying issue.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install beta-agent-memory - After installation, invoke the skill by name or use
/beta-agent-memory - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of beta-agent-memory (v1.0.0) providing long-term memory systems for AI agents.
- Implements episodic, semantic, and procedural memory types.
- Features vector-based memory storage with ChromaDB or Pinecone, entity extraction via spaCy, and conversation summarization.
- Supports persistent context across user sessions, enabling AI agents to recall facts, decisions, and user preferences.
- Includes relevance scoring for memory retrieval and periodic forgetting/summarization of old data.
- Designed for use cases like personal assistants, customer support, research agents, and CRMs.
Metadata
Frequently Asked Questions
What is Beta Agent Memory?
Long-term memory systems for AI agents. Implements vector memory, entity tracking, conversation summarization, and persistent context across sessions. It is an AI Agent Skill for Claude Code / OpenClaw, with 131 downloads so far.
How do I install Beta Agent Memory?
Run "/install beta-agent-memory" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Beta Agent Memory free?
Yes, Beta Agent Memory is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Beta Agent Memory support?
Beta Agent Memory is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Beta Agent Memory?
It is built and maintained by 1477009639zw-blip (@1477009639zw-blip); the current version is v1.0.0.
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