dobv0.0.1

Developers store long-term technical notes about libraries, frameworks, and tools into a layered memory system. Deep-memory holds structured reference files while daily notes stay in the lightweight first layer, enabling fast keyword lookup later.

AI agent builders use this skill to give agents durable recall of concepts, tool usages, and past experiences beyond a single session. The index-based lookup lets agents retrieve exact files without full-text search overhead.

Researchers read articles, blogs, and papers and distill key takeaways into structured markdown files with consistent front-matter sections. Keywords are extracted into an index so future queries resolve to the right file instantly.

Engineering teams maintain a shared workspace of runbooks, API references, and onboarding notes organized by keyword index. New members can ask 'how do I use X' and the agent resolves it from the deep-memory index instead of guessing.

Individuals who want to remember useful knowledge from conversations route long-term concepts into deep-memory while keeping ephemeral facts in daily notes. The decision tree ensures each piece of info lands in the correct layer.

Offer the base deep-memory skill for free while charging for advanced features like automatic index optimization, cloud sync, and multi-agent sharing. Free users get local filesystem storage; paid tiers unlock enhanced retrieval and backup.

Sell a managed version to teams that need shared deep-memory workspaces with role-based access, audit logs, and SSO. The same index-plus-files architecture scales to organization-wide knowledge retention with compliance guarantees.

Bundle the skill as part of a broader agent-building toolkit where persistent layered memory is a headline capability. Developers pay for the toolkit to ship agents that remember technical knowledge reliably across sessions.