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Found 14 Skills
Initialize or migrate a repo into the ai-memory pattern: the .ai-memory.toml routing marker (workspace/project), the recall/write routing snippet in CLAUDE.md/AGENTS.md, and the ai-memory MCP server entry. Includes the qmd→ai-memory migration for repos still on the old wiki/qmd stack. Use when the user asks to set up ai-memory in a project (greenfield or brownfield), wire the MCP, enable auto-capture, or migrate off qmd.
Stores and retrieves persistent memory about records — contacts, companies, employees, members, and more. Handles memorization (single and batch with per-property AI extraction), semantic recall, entity digests, and data export. Use when storing data, syncing records, querying memory, or assembling context for personalization.
Use when working with context management context restore
Automatic context summarization for long-running sessions. Use when context is approaching limits, summarizing completed work, preserving critical information, or managing token budgets.
Show users how Continuous Claude works - the opinionated setup with hooks, memory, and coordination
Save and retrieve memories or embeddings via the repo helpers or API. Use when working with embedding config or memory storage.
Persistent memory for Claude across conversations. Use when starting any task, before writing or editing code, before making decisions, when user mentions preferences or conventions, when user corrects your work, or when completing a task that overcame challenges. Ensures Claude never repeats mistakes and always applies learned patterns.
Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity.
Manage LLMem — structured memory system with SQLite-backed factual memory, semantic search, and background dreaming (decay, boost, promote, merge). Use when the user wants to: (1) add, search, update, or delete memories, (2) generate context for injection, (3) check memory stats, (4) run background consolidation/dream. Triggers on: "memory", "remember", "recall", "llmem", "memories", "forget", "consolidate memories", "dream".
Use to maintain context across sessions - integrates episodic-memory for conversation recall and mcp__memory knowledge graph for persistent facts
Query the memory system for relevant learnings from past sessions
Recall, search, continue, or analyze past conversations. Triggers on recall phrases ("what did we discuss", "continue where we left off", "we decided"), retrospective phrases ("do a retro", "post-mortem", "what went well", "lessons learned", "find antipatterns"), and implicit signals (past-tense references, possessives without context, assumptive questions like "do you remember").