memory-keeperCopy and snapshot all important agent context (MEMORY.md, memory/*.md, AGENTS.md, SOUL.md, etc.) into a dedicated archive directory or repo. Use this skill when you want to back up your memories, context, or configuration files in preparation for maintenance, corruption recovery, or transferring to another host.
Install via ClawdBot CLI:
clawdbot install crimsondevil333333/memory-keeperGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
Post → https://github.com/CrimsonDevil333333/clawdy-memories.gitCalls external URL not in known-safe list
https://github.com/your-org/clawdy-memories.gitAI Analysis
The skill's primary function is to create local backups and optionally push to a user-specified git repository, which is consistent with its stated purpose. The external URLs flagged are examples or user-configurable targets, not hardcoded exfiltration endpoints. The risk is low as the user controls the destination, but there is a potential for misuse if a malicious actor modifies the target repository.
Audited Apr 16, 2026 · audit v1.0
Generated Mar 1, 2026
Before performing system updates or maintenance on an AI agent workspace, administrators use Memory Keeper to create a complete snapshot of all context files. This ensures that if the update corrupts any files, they can be restored from the archive without losing the agent's memory or personality configuration.
When moving an AI agent from one server or development environment to another, Memory Keeper archives all critical context files into a structured format. This allows the agent's complete memory, personality, and configuration to be transferred intact, maintaining continuity across different hosting platforms.
Organizations in regulated industries use Memory Keeper to create timestamped snapshots of AI agent context for compliance purposes. The git integration provides a verifiable audit trail of how the agent's memory and personality evolved over time, which is essential for transparency and regulatory reporting.
Development teams working on AI agents use Memory Keeper to synchronize agent context across team members. By pushing snapshots to a shared git repository, multiple developers can access the same agent memory state, ensuring consistency when testing or modifying the agent's behavior.
Companies running production AI agents implement Memory Keeper as part of their disaster recovery strategy. Regular automated snapshots ensure that if the primary workspace becomes corrupted or inaccessible, the agent can be quickly restored from the latest archive with minimal data loss.
Offer Memory Keeper as free open-source software while providing paid enterprise support, customization services, and premium features. Enterprise clients pay for guaranteed response times, custom integrations with their existing systems, and advanced backup scheduling options.
Host a cloud-based version of Memory Keeper that automatically backs up AI agent contexts to secure cloud storage. Users pay a monthly subscription based on storage volume and retention period, with additional fees for advanced features like automated recovery testing and compliance reporting.
License Memory Keeper's core technology to AI platform providers who want to offer built-in backup capabilities. Charge per-seat or revenue-sharing fees for integration into larger AI development platforms, with additional revenue from training and certification programs for implementation partners.
💬 Integration Tip
Integrate Memory Keeper into existing CI/CD pipelines by adding it as a pre-deployment step, ensuring agent context is backed up before any automated deployment or testing cycle begins.
Scored Apr 16, 2026
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