# SAGE

> Use this tool when you need to enable AI agents to retain institutional memory across conversations, ensuring consistent and reliable decision-making. It solves problems related to knowledge retention, data consistency, and security in multi-agent networks. Ideal for applications requiring persistent memory, fault-tolerant consensus, and real-time visualization, with features like encryption and role-based access control.

Canonical page: https://skillsregistry.net/skills/l33tdawg-sage  
JSON: https://api.skillsregistry.net/v1/skills/l33tdawg-sage

## Description

Provides AI agents with institutional memory that persists across conversations, validated through Byzantine fault-tolerant consensus with confidence scores and natural time decay. Built on CometBFT with 4 application validators (sentinel, dedup, quality, consistency), optional AES-256-GCM encryption, and a CEREBRUM dashboard for real-time visualization. Supports multi-agent networks with RBAC, LAN pairing, and domain-level permissions.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-04-29

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/l33tdawg-sage)
- **Repository:** <https://github.com/l33tdawg/sage>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "l33tdawg-sage"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/l33tdawg-sage` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/l33tdawg-sage/pull`

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