memory

Purpose

Reusable memory helper that routes remember/recall requests to Graphiti MCP while staying model-neutral and providing cache fallback. Always summarizes results into human-readable format.

Triggers

Use when the user says things like: "load memory", "recall notes", "remember", "pull saved context", "fetch past tasks".

How to use

1. •For recall: run lisa memory load --cache [--query <q>] [--limit 10] [--group <id>]. Reads Graphiti facts and prints JSON. Uses cache if MCP is down.
2. •For remember: run lisa memory add "<text>" --cache [--group <id>] [--tag foo] [--source <src>] to append an episode.
3. •Endpoint: reads ${GRAPHITI_ENDPOINT} from .lisa/.env (written by init); group ID is automatically derived from the project folder path. See root AGENTS.md for canonical defaults.
4. •Cache fallback: stored at cache/memory.log inside this skill. On failure, last cached result is returned with status: "fallback".
5. •IMPORTANT: After loading facts, ALWAYS synthesize them into a human-readable summary (see Summarization section below).

Summarization (Required for Recall)

After running the load command, you MUST synthesize the raw JSON facts into a useful summary. Never just show raw JSON to the user.

Summary Structure

Organize facts into these categories (skip empty categories):

1. •Project Overview - What the project is and does
2. •Recent Activity - What was worked on recently (files modified, features added)
3. •Conventions & Patterns - Naming conventions, coding standards, folder structure
4. •Configuration - Docker, environments, tools, dependencies
5. •Milestones - Completed features, important checkpoints
6. •Open Items - Pending tasks, known issues

How to Summarize

• •ALWAYS sort memories by created_at descending (newest first)
• •Group related facts together
• •Use bullet points for clarity
• •Include specific file names and paths when relevant
• •Include the date for each memory (format: "Jan 23" or "Jan 23, 2026")
• •Filter out expired or superseded facts (check expired_at field)
• •Prioritize recent facts over older ones - show newest at top of each section
• •Extract the fact field from each item - that's the human-readable content

Example Output Format

## Memory Summary

**Project:** Lisa - Long-term memory system for Claude Code

**Recent Activity:**
- Modified `src/lib/mcp.ts` for MCP integration
- Updated Docker config to use `zepai/knowledge-graph-mcp:standalone`
- Added init-review script

**Conventions:**
- Files use kebab-case naming
- JavaScript/TypeScript as primary languages

**Configuration:**
- Docker Compose at `.lisa/docker-compose.graphiti.yml`
- Config file: `config-docker-neo4j.yaml`

**Milestones:**
- Memory system reached major milestone (date)

I/O contract (examples)

• •Recall: output JSON { status: "ok", action: "load", group, query, facts: [...] }.
• •Remember: JSON { status: "ok", action: "add", group, text }.
• •Fallback: JSON { status: "fallback", error, fallback: <last cached object> }.

Cross-model checklist

• •Claude: confirm concise trigger phrasing; keep under system limits; avoid markdown-heavy instructions.
• •Gemini: ensure commands are explicit; avoid model-specific tokens; keep JSON small.

Notes

• •All commands use the lisa CLI binary — no scripts to run directly.
• •Facts query defaults to * with max_facts=10; tune via --limit and --query.
• •The fact field in each JSON object contains the human-readable content to summarize.