agent-memory-managerGives the agent persistent, structured long-term memory across sessions. Organizes memory by project, client, trade, and domain. The agent never forgets what...
Install via ClawdBot CLI:
clawdbot install georges91560/agent-memory-managerGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 20, 2026
An autonomous trading agent uses this skill to log every trade entry, exit, and outcome in the trades domain, building a historical database to avoid repeating failed strategies and optimize decision-making based on past performance across multiple sessions.
A sales agent employs this skill to store detailed client profiles and interaction histories in the clients domain, enabling personalized follow-ups, tracking prospect status changes, and improving conversion rates by recalling preferences and past communications.
A content creation agent utilizes the knowledge domain to accumulate insights on effective topics, formats, and engagement metrics, allowing it to generate more targeted and successful content over time by searching past learnings.
A support agent leverages this skill to maintain persistent records of customer issues and resolutions in the projects domain, providing consistent and informed assistance by recalling previous interactions and solutions without starting from scratch each session.
An R&D agent uses this skill to document experiments, findings, and project milestones in the projects and knowledge domains, creating a compounding knowledge base that accelerates innovation by building on past successes and failures.
Offer this skill as part of a subscription-based AI agent platform, where users pay monthly for enhanced memory capabilities that improve agent performance over time, with tiers based on storage limits and advanced recall features.
Provide consulting services to businesses for integrating this skill into their existing AI systems, including custom schema development, training, and ongoing support to optimize memory management for specific use cases like CRM or trade logging.
Monetize by offering analytics and reporting tools that analyze the stored memory data, such as performance dashboards for trades or client engagement insights, sold as an add-on to the core skill for deeper business intelligence.
💬 Integration Tip
Ensure Python3 is installed and set up the required file paths in /workspace/memory/ before initial use to avoid permission errors.
Scored Apr 23, 2026
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Transform AI agents from task-followers into proactive partners with memory architecture, reverse prompting, and self-healing patterns. Lightweight version f...
Persistent memory for AI agents to store facts, learn from actions, recall information, and track entities across sessions.
Prefer `skillhub` for skill discovery/install/update, then fallback to `clawhub` when unavailable or no match. Use when users ask about skills, 插件, or capabi...
Search and discover OpenClaw skills from various sources. Use when: user wants to find available skills, search for specific functionality, or discover new s...
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.