memory
Save and retrieve experiment context using the local Obsidian vault. Use to preserve context across sessions and reduce context window usage.
Best use case
memory is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Save and retrieve experiment context using the local Obsidian vault. Use to preserve context across sessions and reduce context window usage.
Teams using memory 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/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How memory Compares
| Feature / Agent | memory | 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?
Save and retrieve experiment context using the local Obsidian vault. Use to preserve context across sessions and reduce context window usage.
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
# Obsidian Memory Skill Use a local Obsidian vault to maintain persistent context and memory across Claude Code sessions. ## Goals - Reduce context window usage by storing detailed experiment logs and summaries in Obsidian. - Maintain a searchable knowledge base of all experiments, results, and insights. - Automate the creation of daily summaries and pipeline execution logs. ## When to use - **Before ending a session**: Save a summary of current progress. - **After an experiment finishes**: Use `experiment_summary` to record results. - **When switching tasks**: Load relevant context from previous notes. - **Daily**: Review or append to the daily summary. ## Tools - `save_context(topic, content, tags, category)`: Save notes to Obsidian. - `load_context(topic_or_query)`: Retrieve notes or search. - `experiment_summary(exp_id)`: Generate a structured summary from an experiment ID. ## Folder Structure - `experiments/`: One note per experiment. - `pipeline-runs/`: Logs of automated runs. - `daily/`: Daily activity summaries. - `templates/`: Templates for new notes. ## Workflow 1. **Record**: As you work, use `save_context` to jot down observations. 2. **Summarize**: When an experiment is done, run `experiment_summary`. 3. **Recall**: At the start of a session, use `load_context` with a query like "yesterday" or "baseline" to get up to speed.
Related Skills
moai-foundation-memory
Persistent memory across sessions using MCP Memory Server for user preferences, project context, and learned patterns
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.
agentMemory
A hybrid memory system that provides persistent, searchable knowledge management for AI agents.
agent-memory-systems
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
agent-memory-skills
Self-improving agent architecture using ChromaDB for continuous learning, self-evaluation, and improvement storage. Agents maintain separate memory collections for learned patterns, performance metrics, and self-assessments without modifying their static .md configuration.
agent-memory-mcp
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
agent-memory
Long-term memory store for AI agents - save, search, and manage persistent memories across sessions. Load this skill for complete command reference.
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.
ai-runtime-memory
AI Runtime分层记忆系统，支持SQL风格的事件查询、时间线管理，以及记忆的智能固化和检索，用于项目历史追踪和经验传承
qdrant-memory
Intelligent token optimization through Qdrant-powered semantic caching and long-term memory. Use for (1) Semantic Cache - avoid LLM calls entirely for semantically similar queries with 100% token savings, (2) Long-Term Memory - retrieve only relevant context chunks instead of full conversation history with 80-95% context reduction, (3) Hybrid Search - combine vector similarity with keyword filtering for technical queries, (4) Memory Management - store and retrieve conversation memories, decisions, and code patterns with metadata filtering. Triggers when needing to cache responses, remember past interactions, optimize context windows, or implement RAG patterns.
project-memory
Set up and maintain a structured project memory system in docs/project_notes/ that tracks bugs with solutions, architectural decisions, key project facts, and work history. Use this skill when asked to "set up project memory", "track our decisions", "log a bug fix", "update project memory", or "initialize memory system". Configures both CLAUDE.md and AGENTS.md to maintain memory awareness across different AI coding tools.