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AGENT SKILL

simplemem-skill

simplemem-skill 是面向数据与分析的 Agent Skill,来自 aiming-lab/SimpleMem。查看技能说明、操作步骤与使用约定,并通过原项目了解详细用法。

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.

SKILL.md

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namesimplemem-skill
descriptionStore 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.

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).

来源:aiming-lab/SimpleMem · MIT 许可 · 许可原文 · MD 为来源页保存的历史版本