conversation-memory

name	conversation-memory
description	Store and retrieve conversation session context for continuity across sessions (project-level). Saves completed conversations organized by datetime (hour-level granularity) to .cursor/conversations/ and enables loading previous sessions to continue context. Use when the user wants to save a conversation, load a previous session, list past conversations, or continue work from a stored session.

Conversation Memory

Store conversation sessions for later retrieval and continuation. Sessions are organized by datetime at hour-level granularity (YYYY-MM-DD-HH format).

Storage Structure

Sessions are stored in .cursor/conversations/ (project-level) with this structure:

.cursor/conversations/
├── YYYY-MM-DD-HH-session-title.md
├── YYYY-MM-DD-HH-another-session.md
└── ...

Filename format: YYYY-MM-DD-HH-<slugified-title>.md

• Datetime: YYYY-MM-DD-HH (e.g., 2026-02-09-14)
• Title: Slugified from user-provided title or auto-generated from first message

Saving a Conversation

When the user wants to save the current conversation:

1. Generate filename:

   • Extract datetime: current hour in YYYY-MM-DD-HH format
   • Extract title: user-provided title, or generate from first user message (slugify, max 50 chars)
   • Format: YYYY-MM-DD-HH-<title>.md

2. Collect conversation data:

   • Read conversation history from current session
   • Extract all user messages and assistant responses with timestamps
   • Capture workspace context (current directory, project info)
   • Generate summary of key topics and decisions

3. Save conversation:

   • Create .cursor/conversations/ directory if needed (project-level)
   • Write markdown file with frontmatter and full conversation history
   • Use format specified in "Session File Format" section below
   • Handle filename collisions (append -1, -2 if same hour+title exists)

4. Confirm save:

   • Show saved path and filename
   • Display summary of what was saved

Loading a Previous Session

When the user wants to continue from a stored session:

1. List available sessions:

   • Run: python .cursor/skills/lazy-code-skill/conversation-memory/scripts/list_sessions.py (from project root)
   • Shows recent sessions with datetime and title

2. Load session:

   • User selects by filename or datetime
   • Run: python .cursor/skills/lazy-code-skill/conversation-memory/scripts/load_session.py <filename> (from project root)
   • Display conversation history and context
   • Continue from where it left off

Searching Sessions

To find sessions by date, title, or content:

• Run: python .cursor/skills/lazy-code-skill/conversation-memory/scripts/search_sessions.py <query> (from project root)
• Returns matching sessions with preview

Session File Format

Each saved session uses this structure:

---
saved_at: YYYY-MM-DD HH:MM:SS
session_start: YYYY-MM-DD HH:MM:SS
title: Session Title
summary: Brief summary of conversation topics
---

# Conversation Session: [Title]

## Context
[Any relevant context, workspace info, or initial state]

## Messages

### User: [timestamp]
[User message content]

### Assistant: [timestamp]
[Assistant response]

...

Utility Scripts

The agent can use these scripts or implement the logic directly:

save_session.py: Template script for saving (agent should write markdown directly)

# Run from project root
python .cursor/skills/lazy-code-skill/conversation-memory/scripts/save_session.py [--title "Title"]

list_sessions.py: List all saved sessions

# Run from project root
python .cursor/skills/lazy-code-skill/conversation-memory/scripts/list_sessions.py [--limit N] [--date YYYY-MM-DD]

load_session.py: Load and display a session

# Run from project root
python .cursor/skills/lazy-code-skill/conversation-memory/scripts/load_session.py <filename>

search_sessions.py: Search sessions by content

# Run from project root
python .cursor/skills/lazy-code-skill/conversation-memory/scripts/search_sessions.py <query>

Note: The agent should write markdown files directly when saving, using the conversation history available in the current session context.

Workflow Examples

Saving at end of session:

• User: "Save this conversation"
• Agent saves with auto-generated title from first message
• Confirms save location

Continuing previous work:

• User: "Load yesterday's conversation about the API"
• Agent lists recent sessions
• User selects or agent finds matching session
• Agent loads and displays context
• Conversation continues

Finding old sessions:

• User: "Show me conversations from last week about authentication"
• Agent searches by date and content
• Displays matching sessions