agent-mementoTick-Driven Autonomous Production Factory for LLMs. A framework for long-running agents using Cron/Heartbeats and physical Markdown checklists to prevent OOM...
Install via ClawdBot CLI:
clawdbot install yangwenyu2/agent-mementoGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
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https://img.shields.io/badge/OpenClaw-Skill-blue.svgAudited Apr 17, 2026 · audit v1.0
Generated Mar 22, 2026
Manages long-term software projects by breaking them into small, verifiable tasks executed automatically. Prevents LLM memory issues and ensures consistent progress through tick-driven execution.
Handles large-scale content creation, such as generating documentation or marketing materials, by structuring tasks into phases and verifying outputs automatically to maintain quality and coherence.
Automates data analysis and report generation in research projects, using tick workers to process batches of data and update status files, reducing manual oversight and errors.
Orchestrates infrastructure deployments and maintenance tasks by scheduling cron jobs to execute scripts, monitor progress, and log results, ensuring reliability and traceability.
Automates updates to product listings, pricing, and inventory by breaking changes into tasks, verifying each update, and maintaining a clear audit trail through physical files.
Offers a cloud-based platform with dashboard monitoring and automated tick execution, charging monthly fees based on project size and number of tasks. Targets teams needing continuous project automation.
Provides tailored setup and integration services for enterprises, including custom scripts and training. Generates revenue through one-time project fees and ongoing support contracts.
Distributes the core framework as open source to build community adoption, while monetizing advanced features like enhanced dashboards, analytics, and priority support through a freemium model.
💬 Integration Tip
Ensure all required binaries (bash, openclaw, node, npm, git) are installed and accessible in the system PATH before initializing the skill to avoid execution errors.
Scored Apr 19, 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.
Search and discover OpenClaw skills from various sources. Use when: user wants to find available skills, search for specific functionality, or discover new s...
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...
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.