benos-memory-core
Core runtime/volatile memory module for BenOS agent environment. Use to: store and retrieve active session state, open loops, decisions, and scratch notes at runtime.
Best use case
benos-memory-core is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Core runtime/volatile memory module for BenOS agent environment. Use to: store and retrieve active session state, open loops, decisions, and scratch notes at runtime.
Teams using benos-memory-core should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/benos-memory-core/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How benos-memory-core Compares
| Feature / Agent | benos-memory-core | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Core runtime/volatile memory module for BenOS agent environment. Use to: store and retrieve active session state, open loops, decisions, and scratch notes at runtime.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
AI Agents for Coding
Browse AI agent skills for coding, debugging, testing, refactoring, code review, and developer workflows across Claude, Cursor, and Codex.
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
Top AI Agents for Productivity
See the top AI agent skills for productivity, workflow automation, operational systems, documentation, and everyday task execution.
SKILL.md Source
# BenOS Memory Core **Purpose:** - Interface for runtime/volatile memory for BenOS agents and submodules. - Store session info, open loops, decisions, and notes through index.js commands or direct file edits. **State/storage location:** - Default: `~/.openclaw/workspace/benos/runtime/state.json` - Convention: Also supports related runtime and session files under `benos/runtime/`. **Usage:** - Use skill commands for agent-controlled read/write. - Edit files directly for manual repairs or migration as needed. **Schema v1:** - schemaVersion: number - lastHydratedAt: ISO8601 or null - lastSessionRef: string or null - activeInitiatives: array - openLoops: array - recentDecisions: array - notes: array **Extension:** Add new fields via additional versioned schemas or skill upgrades as needed.
Related Skills
Lead Scorer
Score and qualify leads using customizable criteria. Prioritize your pipeline by fit, intent, and engagement to focus on deals most likely to close.
Hiring Scorecard Skill
Score and compare job candidates objectively using weighted criteria. Eliminates gut-feel hiring decisions.
Agent Memory Architecture
Complete zero-dependency memory system for AI agents — file-based architecture, daily notes, long-term curation, context management, heartbeat integration, and memory hygiene. No APIs, no databases, no external tools. Works with any agent framework.
memory-cache
High-performance temporary storage system using Redis. Supports namespaced keys (mema:*), TTL management, and session context caching. Use for: (1) Saving agent state, (2) Caching API results, (3) Sharing data between sub-agents.
Memory
Infinite organized memory that complements your agent's built-in memory with unlimited categorized storage.
auto-memory
Indestructible agent memory — permanently stored, never lost. Save decisions, identity, and context as a memory chain on the Autonomys Network. Rebuild your full history from a single CID, even after total state loss.
Triple-Layer Memory System
三层记忆系统 - 解决 AI Agent 长对话记忆丢失和上下文管理问题
agent-memory-os
Stop agents from "forgetting, mixing projects, and rotting over time" by giving them a practical memory operating system: global memory, project memory, promotion rules, validation cases, and a maintenance loop.
tricore
TriCore Architecture - A deterministic (Code-First) three-layer memory and cognitive framework designed for low-resource servers/Agents. It includes the underlying memctl engine, system policy constraints (Linter), and a fully refactored suite of cognitive tools for planning (Planning), reasoning (ReAct), and self-evolution (Self-Evolution).
fitclaw-public-core
Public-safe FitClaw coaching workflow covering onboarding, hydration, nutrition, and training structure. Use when demonstrating a reusable AI fitness coaching method without exposing private user data or live production configuration.
elite-longterm-memory
Ultimate AI agent memory system with WAL protocol, vector search, git-notes, and cloud backup. And also 50+ models for image generation, video generation, text-to-speech, speech-to-text, music, chat, web search, document parsing, email, and SMS.
memory-agent
维护用户审美偏好与创作历史，为其他 Agent 提供可复用的风格参考。当开始新任务或用户表达喜好时触发。