memory-capture
Capture and organize memories, decisions, and learnings to a memories.md file. Use when you want to save context for future sessions.
Best use case
memory-capture is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Capture and organize memories, decisions, and learnings to a memories.md file. Use when you want to save context for future sessions.
Teams using memory-capture should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/memory-capture/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How memory-capture Compares
| Feature / Agent | memory-capture | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Capture and organize memories, decisions, and learnings to a memories.md file. Use when you want to save context for future sessions.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Memory Capture Help users capture important decisions, preferences, and learnings to their memories file for future reference. ## When to Use Invoke this skill when the user wants to: - Record a decision they made - Save a preference for future sessions - Document something they learned - Create a note about the project or codebase ## Memory Locations - **Personal memories**: `~/.factory/memories.md` - preferences that apply across all projects - **Project memories**: `.factory/memories.md` - decisions specific to the current project ## Capture Process ### Step 1: Understand What to Remember Ask the user to clarify: - What specifically should be remembered? - Is this a personal preference or project-specific? - What's the context (why is this worth remembering)? ### Step 2: Categorize the Memory Common categories: **For Personal Memories:** - Code style preferences - Tool preferences - Communication style - Workflow patterns **For Project Memories:** - Architecture decisions - Design choices - Domain knowledge - Known issues - Team conventions ### Step 3: Format the Entry Use this format: ```markdown ### [Date]: [Short Title] **Category**: [Decision/Preference/Learning/Context] **Summary**: [One sentence description] **Details**: [Full explanation if needed] **Reasoning**: [Why this matters - optional] ``` For simpler entries: ```markdown - [Date] [Category]: [Description] ``` ### Step 4: Append to Memories File Add the formatted entry to the appropriate memories file. If the file doesn't exist, create it with proper structure: **For Personal (~/.factory/memories.md):** ```markdown # My Development Memory ## Preferences [preferences entries] ## Learnings [learning entries] ``` **For Project (.factory/memories.md):** ```markdown # Project Memory ## Decisions [decision entries] ## Context [context entries] ## Known Issues [issue entries] ``` ## Example Captures ### Architecture Decision User says: "Remember that we chose PostgreSQL over MongoDB for this project" Capture as: ```markdown ### 2024-02-15: Database Selection **Category**: Architecture Decision **Summary**: Chose PostgreSQL over MongoDB for the primary database **Reasoning**: - Strong relational data model fits our domain - ACID compliance needed for financial transactions - Team has more PostgreSQL experience - Better tooling for complex queries and reporting ``` ### Personal Preference User says: "I prefer early returns over nested conditionals" Capture as: ```markdown ## Code Style Preferences - [2024-02-15] I prefer early returns over nested conditionals for better readability ``` ### Domain Knowledge User says: "Note that free tier users are limited to 3 team members" Capture as: ```markdown ### Business Rules - Free tier: Limited to 3 team members - Pro tier: Up to 20 team members - Enterprise: Unlimited team members ``` ### Technical Context User says: "The auth service has a known issue with refresh tokens (#234)" Capture as: ```markdown ## Known Issues - [ ] Auth refresh token race condition (#234) - Can cause session loss during concurrent requests ``` ## Tips 1. **Keep entries scannable** - Use headers and bullet points 2. **Include dates** - Context matters, decisions may change 3. **Note the "why"** - Future you will want to know 4. **Link to issues/PRs** - For traceability 5. **Review periodically** - Archive outdated memories --- ## Alternative Implementations This skill is one of three ways to capture memories. Choose based on your workflow: ### Option 1: This Skill (Interactive) Droid invokes this skill when you ask to remember something. Best when you want help categorizing and formatting memories. **Usage:** "Remember that we chose PostgreSQL for ACID compliance" ### Option 2: Hook (Automatic) A [UserPromptSubmit hook](/cli/configuration/hooks-guide) that triggers on phrases like "remember this:". Best for zero-friction capture. See the [Memory Management guide](/guides/power-user/memory-management#automatic-memory-capture) for the hook implementation. **Usage:** "Remember this: we use the repository pattern for data access" ### Option 3: Custom Slash Command (Manual) A [custom slash command](/cli/configuration/custom-slash-commands) for quick, consistent capture. Create `~/.factory/commands/remember.md`: ```markdown --- description: Save a memory to your memories file argument-hint: <what to remember> --- Add this to my memories file (~/.factory/memories.md): $ARGUMENTS Format it appropriately based on whether it's a preference, decision, or learning. Include today's date. ``` **Usage:** `/remember we chose PostgreSQL for ACID compliance` ### Comparison | Approach | Trigger | Best For | |----------|---------|----------| | **Skill** | Droid decides | Interactive categorization | | **Hook** | Automatic on keywords | Zero-friction capture | | **Slash Command** | You type `/remember` | Quick manual capture |
Related Skills
moai-foundation-memory
Persistent memory across sessions using MCP Memory Server for user preferences, project context, and learned patterns
memorylane
Zero-config persistent memory for Claude with automatic cost savings. Use when you need to remember project context, reduce API token costs, track learned patterns, manage memories across sessions, or curate/clean up memories. Automatically compresses context 6x and saves 84% on API costs. Keywords: memory, remember, recall, context, cost savings, reduce tokens, learn, patterns, insights, curate, clean up memories, review memories.
memory-sync
Guided workflow for maintaining strategic redundancy between Serena memories and project documentation. Use after significant code changes, phase completions, or when new architectural patterns are discovered.
memory-management
Guide for managing Claude Code memory effectively. Use when setting up project memory, optimizing CLAUDE.md files, configuring rules directories, or establishing cross-session knowledge patterns. Covers memory hierarchy, best practices, and context optimization.
memory
Manages memory, SSOT files, and Plans.md operations. Use when user mentions メモリ, memory, SSOT, decisions.md, patterns.md, マージ, merge, Plans.md, 移行, migrate. Do NOT load for: 実装作業, レビュー, 一時的なメモ, セッション中の作業記録.
memory-conventions
This skill should be used when persisting context between sessions, saving project state, loading previous session context, or managing longitudinal memory beyond beads issue tracking.
memory-bank
Persistent project documentation system that maintains context across sessions. Creates structured Memory Bank files to preserve project knowledge, decisions, and progress.
context-memory
Advanced context and memory management system for AI agents. Provides persistent memory across sessions through daily logs (memory/YYYY-MM-DD.md), long-term curated memory (MEMORY.md), conversation archives with semantic search, and automatic behavioral learning from user satisfaction tracking. Use when you need to: (1) Remember information across sessions, (2) Archive conversations before context loss, (3) Search past discussions, (4) Track and learn from user satisfaction patterns, (5) Maintain session continuity, (6) Implement proactive memory maintenance. Includes conversation-archiver.py and satisfaction-tracker.py scripts, session startup routines, and periodic reflection workflows.
ac-memory-manager
Manage persistent memory for autonomous coding. Use when storing/retrieving knowledge, managing Graphiti integration, persisting learnings, or accessing episodic memory.
atuin-memory
Check, store, and retrieve project memories from atuin kv. Use when starting work on a project, recalling previous context, storing plans or specs, or when the user mentions memory, atuin, or project context.
memory-safety-patterns
Implement memory-safe programming with RAII, ownership, smart pointers, and resource management across Rust, C++, and C. Use when writing safe systems code, managing resources, or preventing memory...
helix-memory
Long-term memory system for Claude Code using HelixDB graph-vector database. Store and retrieve facts, preferences, context, and relationships across sessions using semantic search, reasoning chains, and time-window filtering.