simplemem-skill
Enables the AI to remember important information and context across different chat sessions.
Install
mkdir -p .claude/skills/simplemem-skill && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4593" && unzip -o skill.zip -d .claude/skills/simplemem-skill && rm skill.zipInstalls to .claude/skills/simplemem-skill
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Store and retrieve conversation memories across sessions. Use when asked to 'remember this', 'save conversation', 'add to memory', 'what did we discuss about...', 'query memories', or 'import chat history'. Also use proactively to preserve important dialogue context and decisions.Key capabilities
- →Add dialogue to memory
- →Query past conversations
- →Retrieve raw memory
- →Maintain memory statistics
- →Clear all memories
How it works
It stores and retrieves conversation data using a persistent memory layer, allowing for semantic queries across sessions.
Inputs & outputs
When to use simplemem-skill
- →Storing project decisions
- →Recalling specific user preferences
- →Preserving context from long-running discussions
- →Querying history for past tasks
About this skill
SimpleMem Skill
Persistent conversational memory across sessions.
Proactive Usage
Save memories when discovering valuable dialogue:
- Important decisions or commitments made in conversation
- Complex information that may be referenced later
- Context from long discussions worth preserving
- Solutions to problems that took effort to uncover
Check memories before:
- Answering questions about past conversations
- Resuming work from previous sessions
- Building on earlier discussion topics
Quick Start
# Add a dialogue
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py add --speaker "Alice" --content "Meet Bob tomorrow at 2pm"
# Query memories
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py query --question "When should Alice meet Bob?"
Operations
Save
Add single dialogue:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py add --speaker "User" --content "Your message here"
With timestamp (ISO 8601):
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py add --speaker "Alice" --content "Message" --timestamp "2026-01-17T14:00:00Z"
Query
Semantic query with answer:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py query --question "What did Alice say about meetings?"
With reflection for deeper analysis:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py query --question "Your question" --enable-reflection
Raw retrieval:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py retrieve --query "Alice meetings" --top-k 5
Maintain
View statistics:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py stats
Clear all memories:
# Use with caution - irreversible
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py clear --yes
Batch Import
For importing conversation histories from JSONL files, see references/import-guide.md.
Custom Table Names
Use different tables to organize conversation contexts:
python ~/.claude/skills/simplemem-skill/scripts/cli_persistent_memory.py --table-name my_custom_table add --speaker "User" --content "Message"
Data Format
All dialogues are stored with:
speaker: Who said it (string)content: What was said (string)timestamp: When it was said (ISO 8601 datetime, auto-generated if omitted)
Advanced Usage
For detailed information:
- OpenRouter setup and model selection: references/openrouter-guide.md
- JSONL import format and batch operations: references/import-guide.md
- CLI command reference: references/cli-reference.md
- System architecture and configuration: references/architecture.md
Setup
Install dependencies:
cd ~/.claude/skills/simplemem-skill
pip install -r requirements.txt
Configure OpenRouter API:
cp src/config.py.example src/config.py
# Edit src/config.py and set your OPENROUTER_API_KEY
See references/openrouter-guide.md for API key setup and model customization.
Data storage: Memories persist in data/lancedb/ (auto-created).
When not to use it
- →For transient data that does not need persistence
- →For sensitive data requiring strict deletion policies
Prerequisites
Limitations
- →Requires OpenRouter API key
- →Clear operation is irreversible
How it compares
It provides cross-session persistence compared to standard session-limited memory.
Compared to similar skills
simplemem-skill side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| simplemem-skill (this skill) | 1 | 6mo | Review | Intermediate |
| skills | 0 | 4mo | Review | Intermediate |
| ai-partner-chat | 1 | 7mo | Review | Intermediate |
| prompt-optimizer | 43 | 6mo | No flags | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
You might also like
skills
alejopuentes1-maker
Skill personalizado para crear síntesis automáticas de sesiones y sincronizarlas con NotebookLM.
ai-partner-chat
eze-is
基于用户画像和向量化笔记提供个性化对话。当用户需要个性化交流、上下文感知的回应,或希望 AI 记住并引用其之前的想法和笔记时使用。
prompt-optimizer
solatis
Optimize system prompts for Claude Code agents using proven prompt engineering patterns. Use when users request prompt improvement, optimization, or refinement for agent workflows, tool instructions, or system behaviors.
transcribe
openai
Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.
diary
Anhvu1107
ALWAYS use this when the request matches Diary: Unified Diary System: A context-preserving automated logger for multi-project development.
long-audio-transcript-processor
cafe3310
对大量语音转写稿进行校对、整理、分段处理,支持断点续传和恢复