auto-dream-lightLightweight, memory-safe Auto Dream workflow for OpenClaw that consolidates recent notes into existing memory files without replacing the user’s current memo...
Install via ClawdBot CLI:
clawdbot install mrgyan/auto-dream-lightGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Oct 6, 2026
An individual knowledge worker uses the skill once a day or on demand to scan their daily notes in memory/YYYY-MM-DD.md and extract durable facts, preferences, and reusable lessons into MEMORY.md and project files. This keeps their OpenClaw memory tidy without forcing a new folder structure or dashboard. The dream log provides a lightweight audit trail of what changed.
A small software team uses Auto Dream Light to consolidate project-specific decisions, architecture notes, and runbooks from daily standup logs into memory/projects/** files. Since the skill favors project files over stuffing everything into MEMORY.md, each project folder remains the source of truth. Developers can review the dream log to see what was merged and when.
A solo consultant running multiple client engagements uses the skill to sort recent daily notes into per-client project memory folders while preserving stable client preferences in MEMORY.md. It skips low-value chat and one-off noise, so only durable engagement facts are retained. A concise summary is returned after each run for quick client review.
A researcher uses the skill to periodically consolidate experiment logs, paper notes, and idea fragments into long-term memory without rebuilding their existing note system. Durable conclusions and stable observations are routed to MEMORY.md, while project-specific context stays in memory/projects/** folders. The dream log helps track how the research memory evolved over time.
An operations team starts with manual dream runs and gradually moves toward a fixed trigger-based flow using references/semi-auto.md, with a path to cron later. The skill scans recent daily incident and handover notes, extracts reusable lessons, and updates the correct memory files. The team keeps the existing MEMORY.md structure and reviews the dream log for compliance and continuity.
The base Auto Dream Light skill is offered for free to individual OpenClaw users, while advanced features like semi-automatic triggers, extended dream-log analytics, or managed cron setup are sold as a paid upgrade. This lowers adoption friction and monetizes teams that want more automation. Revenue comes from monthly or annual subscriptions to the premium tier.
A service provider installs and configures Auto Dream Light for teams, helping them design their memory routing rules and semi-automatic triggers without replacing their existing structure. The provider offers ongoing monitoring, tuning, and audits of the dream log for clients who want memory hygiene handled for them. This is a high-touch B2B offering for organizations with large OpenClaw memory stores.
The skill is white-labeled and bundled as a lightweight memory-consolidation add-on inside existing knowledge management or note-taking platforms that integrate with OpenClaw. Platform vendors pay a licensing fee to embed the conservative dream workflow, which works with users' existing MEMORY.md and memory/ folders. End users get the feature as part of their platform subscription.
💬 Integration Tip
Start by running the skill manually with references/manual-run.md to observe how it routes durable facts into your existing MEMORY.md and project folders. Only move to trigger-based or cron flows after reviewing several dream logs and confirming the conservative updates match your expectations.
Scored Oct 6, 2026
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