Results for “memory-acquisition”

Merges mature lessons from a domain memory file into its instruction file, preserving knowledge with minimal redundancy.

Stores, retrieves, and curates persistent facts in a structured memory map, distinguishing between user facts and reference text.

Captures notes locally, organizes them by topic and project, and retrieves relevant notes on demand, including meeting preparation and idea synthesis.

Retrieve task-relevant project and global memory without loading everything. Load when the user asks what we decided, recall prior context, find memory about a feature, explain past rationale, resume a task, or check deferred ideas.

Provides persistent, compounding memory for AI agents across sessions using local markdown files, with optional Supabase-backed semantic search.

Consolidates auto-memory files in ~/.claude/projects by auditing, planning, and executing a 4-phase cleanup with user approval.

Persists and recalls agent knowledge across sessions using four approaches: static KB, company wiki, persistent memory, and session brain.

Watches conversations continuously and compresses them into prioritized notes, consolidating and recovering missed sessions with multiple redundancy layers.

Builds a personal knowledge base for capturing and retrieving understanding, with structured namespaces for concepts, tools, patterns, and references.

Manages a multi-layered knowledge system for ingesting, organizing, syncing, and retrieving knowledge across local files, MCP memory, vector stores, and Git repos.