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synapse-layer突触层

Agent Skill

synapse-layer 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,755

周安装

71

GitHub Stars

公开资料未说明

下载量

551
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:synapse-layer(突触层)
来源仓库:https://github.com/rafacpti23/synapse-layer
安装命令:
openclaw skills install synapse-layer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install synapse-layer

简介

提供持久、加密的 AI 代理内存和 4 层安全管道,用于存储、检索、共享和分析代理内存。

SKILL.md

name
synapse-layer
description
Persistent memory infrastructure for AI agents with 4-layer Cognitive Security Pipeline (PII redaction, AES-256-GCM encryption, intent validation, differential privacy). Use when: configuring SynapseLayer MCP integration, storing/retrieving agent memories, cross-agent memory sharing, analyzing trust scores, or implementing persistent memory in OpenClaw agents. Also use for troubleshooting SynapseLayer connectivity, understanding Trust Quotient scoring, or setting up framework integrations (LangChain, CrewAI, AutoGen, LlamaIndex, Semantic Kernel).

Synapse Layer Skill

Synapse Layer provides persistent, encrypted memory for AI agents with a 4-layer security pipeline.

Quick Setup

Python SDK (Recommended for OpenClaw)

Install and use:

pip install synapse-layer
from synapse_test import SynapseClient

client = SynapseClient(api_key="sk_connect_...")

# Save memory
result = client.remember("User prefers dark mode", agent="mel")

# Retrieve memories
memories = client.recall("user preferences", agent="mel")

See scripts/synapse_client.py for a complete client implementation.

MCP Integration (External Tools)

Add to OpenClaw gateway config for external MCP clients:

{
  "mcp": {
    "servers": {
      "synapse-layer": {
        "url": "https://forge.synapselayer.org/mcp",
        "headers": {
          "Authorization": "Bearer sk_connect_YOUR_API_KEY"
        }
      }
    }
  }
}

Note: This is for external MCP clients (Claude Desktop, Cursor) to connect to SynapseLayer, not for OpenClaw agents to use directly.

Available Tools

Once configured via Python SDK, these operations are available:

  • save_to_synapse - Store memory with full security pipeline
  • recall - Retrieve memories ranked by Trust Quotient™
  • search - Cross-agent memory search with full-text matching
  • process_text - Auto-detect decisions, milestones, and alerts
  • health_check - System health, version, and capability report

Cognitive Security Pipeline

Every memory passes through 4 non-bypassable layers:

  1. Semantic Privacy Guard™ - 15+ regex patterns detect PII, secrets, credentials
  2. Intelligent Intent Validation™ - Two-step categorization with self-healing
  3. AES-256-GCM Encryption - Authenticated encryption with PBKDF2 key derivation
  4. Differential Privacy - Calibrated Gaussian noise on embeddings

Key Concepts

Trust Quotient™ (TQ)

Score (0-1) ranking memory reliability. Higher TQ = more trusted memory.

Cross-Agent Memory

Memories can be shared across agents using the same agent_id or cross-agent search.

Storage Backends

  • Remote (Forge) - PostgreSQL via forge.synapselayer.org (recommended)
  • SQLite - Local .synapse/memories.db (requires local setup)

Usage Patterns

Basic Memory Operations

Use the Python SDK client:

from scripts.synapse_client import SynapseClient

client = SynapseClient(api_key="sk_connect_...")

# Save
client.remember("Important decision", agent="mel", importance=5)

# Recall
memories = client.recall("recent decisions", agent="mel", limit=5)

# Search
all_memories = client.search("project deadlines", limit=10)

Process Text Automatically

Extract events from free-form text:

events = client.process_text(
    "Decided to use PostgreSQL. Deadline is May 1st.",
    agent="hermes",
    project="website-redesign"
)

Security Considerations

Data Privacy

  • PII automatically redacted before storage
  • All data encrypted at rest (AES-256-GCM)
  • Differential privacy protects individual entries
  • Zero-knowledge architecture

Resilience Strategy

Recommended approach for production:

  1. Use SynapseLayer as primary memory store
  2. Keep OpenClaw's MEMORY.md/memory/ as backup
  3. Monitor service health via health_check
  4. Have fallback procedure if service unavailable

Troubleshooting

Connection Issues

  1. Run health_check to verify connectivity
  2. Verify API key is valid
  3. Check network access to forge.synapselayer.org

Memory Not Persisting

  1. Check API key permissions
  2. Verify security pipeline didn't reject content
  3. Review Trust Quotient in response

Low Trust Quotient

  1. Review security pipeline logs
  2. Increase confidence/importance scores
  3. Check if content was sanitized

Testing

Use the test script:

python3 /app/skills/synapse-layer/scripts/synapse_test.py

This script verifies:

  • Service connectivity (health_check)
  • Basic save operations
  • Memory retrieval
  • Cross-agent search

Reference Documentation

For more details, see:

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

73.16%
按下载量换算403

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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