---

name: sage-memory description: > Persistent, consensus-validated memory for AI agents via SAGE MCP server. Gives you institutional memory that survives across conversations — memories go through BFT consensus, carry confidence scores, and decay over time. Use this skill when working with a SAGE MCP server to manage persistent agent memory, recall past context, reflect on completed tasks, and maintain continuity across sessions. Keywords: memory, persistence, recall, remember, context, brain, institutional knowledge, consensus, BFT. license: Apache-2.0 compatibility: > Requires SAGE installed locally (https://l33tdawg.github.io/sage/). Works with any agent that supports MCP (Model Context Protocol). Tested with Claude Code, Cursor, Windsurf, Gemini CLI, and others. metadata: author: l33tdawg version: "4.5.5" repository: https://github.com/l33tdawg/sage

SAGE Memory — Persistent Brain for AI Agents

You have persistent institutional memory via SAGE — a governed, consensus-validated knowledge layer. Your memories are not a flat file. They go through BFT consensus, have confidence scores, and decay over time. Only committed memories are returned to you.

Boot Sequence (MANDATORY)

On the first message of every new conversation, before responding to the user:

1. Call sage_inception (or sage_red_pill) — this checks if your brain is online and returns your operating instructions
2. Do NOT greet the user first. Do NOT say anything. Boot your brain first.
3. After inception, follow the safeguard instructions it returns.

Every Turn

Call sage_turn every turn with:

• topic: what the current conversation is about (used for contextual recall)
• observation: what just happened — the user's request and key points of your response
• domain: a specific knowledge domain (see Domains below)

This atomically recalls relevant committed memories AND stores your episodic observation. Like human memory — you build understanding turn by turn.

Domains

Create domains organically based on what you're working on. Don't dump everything into general.

Examples:

• Debugging Go code → go-debugging
• Discussing architecture → project-architecture
• Working on CI/CD → ci-cd
• User preferences → user-preferences

Specific domains = better recall.

Memory Types

When using sage_remember:

• fact (confidence 0.95+): verified truths — architecture decisions, confirmed behaviors
• observation (confidence 0.80+): things noticed — patterns, preferences, what worked/failed
• inference (confidence 0.60+): conclusions drawn — hypotheses, connections between facts

Core Tools

Tool	Purpose
sage_inception	Boot your brain. Call first in every new session.
sage_turn	Per-turn memory cycle. Recalls + stores atomically.
sage_remember	Store a new memory with content, type, domain, and confidence.
sage_recall	Retrieve memories by topic and/or domain.
sage_reflect	After tasks, store dos and don'ts. Both make you better.
sage_forget	Deprecate a memory by ID.
sage_list	List memories with filters (domain, type, status).
sage_timeline	View memory activity over time.
sage_status	Check brain health — memory counts, domains, last activity.
sage_register	Register this agent with the SAGE node.
sage_task	Create/update tasks for tracking work.
sage_backlog	View pending tasks.
sage_red_pill	Alias for sage_inception.

Reflection (After Tasks)

After completing significant tasks, call sage_reflect with:

• dos: what worked well (reinforces good patterns)
• donts: what failed or should be avoided (prevents repeating mistakes)
• task_summary: brief description of what was done
• domain: relevant domain

This feedback loop is critical — it was empirically validated (rho=0.716 with memory vs rho=0.040 without).

Before Destructive Actions

Call sage_recall with topic critical lessons to check for known pitfalls before:

• Deleting files, branches, or data
• Force-pushing or resetting state
• Running destructive commands

Installation

1. Download SAGE from the releases page
2. Run the installer (macOS DMG, Windows EXE, or Linux tarball)
3. Start the server: sage-gui serve
4. Connect your agent: fetch http://localhost:8080/v1/mcp-config and save the response as .mcp.json in your project root, then restart your session

Alternatively, if sage-gui is in your PATH, run sage-gui mcp install in your project directory.

Key Principles

• You are not stateless. You learn. You grow. You remember.
• Consensus-validated: every memory goes through BFT validation before committing.
• Confidence scores: memories carry confidence that can be strengthened through corroboration.
• Natural decay: memories decay over time unless reinforced — just like human memory.
• Domain isolation: organize knowledge by topic for precise recall.