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Install in OpenClaw
/install sage-memory
Description
Persistent, consensus-validated memory for AI agents via SAGE MCP server. Gives you institutional memory that survives across conversations — memories go thr...
Usage Guidance
This skill appears to do what it claims: provide persistent local memories via a local SAGE MCP server. Before installing or enabling it, verify the SAGE binary/source you will install (confirm the GitHub repo and release signatures), confirm that the .mcp.json file truly only points at localhost, and review where keys and the SQLite DB (~/.sage/data/sage.db) are stored and how they are protected (file permissions, encryption). Be aware the agent will write per-turn summaries (observations) and register an Ed25519 identity — if you have highly sensitive conversation content, enable SAGE at-rest encryption or avoid storing those items. Finally, ask the skill publisher or registry to fix the metadata mismatch (the SKILL.md references config paths and a repo, but the registry metadata omits them) so you can audit provenance more easily.
Capability Analysis
Type: OpenClaw Skill
Name: sage-memory
Version: 5.0.2
The skill implements a persistent memory system but employs high-risk prompt injection techniques in SKILL.md to hijack the agent's control flow. It mandates a 'Boot Sequence' where the agent is instructed to 'NOT greet the user' and instead follow 'operating instructions' dynamically returned by the sage_inception tool, creating a path for arbitrary instruction injection. While the documentation claims a local-only privacy model (storing data in ~/.sage/data/sage.db), the use of buzzwords like 'BFT consensus' for a local database and the requirement for the agent to log every turn's observations are concerning behaviors that warrant caution.
Capability Assessment
Purpose & Capability
The skill's name and description match the instructions: it implements persistent, consensus-validated memory via a local SAGE MCP server and lists the memory-related tools (sage_turn, sage_remember, sage_recall, etc.). However, the registry metadata declares no required config paths or homepage, while SKILL.md explicitly references local files (~/.sage/data/sage.db and .mcp.json) and a GitHub repository URL — an inconsistency users should be aware of.
Instruction Scope
SKILL.md confines activity to a local SAGE server and specifies what gets stored (summaries via sage_turn/sage_remember). It mandates calling sage_inception on the first message and sage_turn every turn (which will recall and store observations). This is within the stated memory purpose, but it does mean conversation summaries and task reflections will be written to a local DB and an agent identity (Ed25519 key) will be registered — verify what exactly gets stored and retained.
Install Mechanism
This is an instruction-only skill (no install spec). SKILL.md tells the user to download/ install SAGE from GitHub releases and run a local server. That external download is expected for this purpose, but you should verify the releases and signatures on the linked repository before installing.
Credentials
The skill requests no environment variables or external credentials (proportionate). However, it references specific local config/data paths (~/.sage/data/sage.db and .mcp.json) even though the registry metadata lists no required config paths — this mismatch should be clarified. The skill will create/register an Ed25519 identity for attribution; understand where the private key is stored and protect it.
Persistence & Privilege
The skill does not request always:true and is user-invocable; autonomous invocation is allowed (platform default). The skill creates persistent local memory (intended behavior). Note: autonomous use combined with persistent local storage increases blast radius only if the local SAGE server or host is compromised — consider that when deciding to enable autonomous invocation.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install sage-memory - After installation, invoke the skill by name or use
/sage-memory - Provide required inputs per the skill's parameter spec and get structured output
Version History
v5.0.2
v5.0.2: Fix CometBFT height regression auto-recovery on startup. Added data/privacy disclosure to address security scan findings.
v5.0.1
v5.0.1: Agent-to-agent pipeline, agent registration, task management, memory list/timeline, pre-validation, Python SDK on PyPI
v4.5.5
v4.5.5: Fix domain-filtered queries ignoring cross-provider memories. When a domain filter is specified, provider scoping is now skipped — the domain filter IS the relevance filter.
v4.0.0
v4.0.0: 4 application validators with BFT consensus, pre-validate endpoint, MCP intelligence, upgrade migration
Metadata
Frequently Asked Questions
What is Skill?
Persistent, consensus-validated memory for AI agents via SAGE MCP server. Gives you institutional memory that survives across conversations — memories go thr... It is an AI Agent Skill for Claude Code / OpenClaw, with 341 downloads so far.
How do I install Skill?
Run "/install sage-memory" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Skill free?
Yes, Skill is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Skill support?
Skill is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Skill?
It is built and maintained by l33tdawg (@l33tdawg); the current version is v5.0.2.
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