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Biomorphic Memory

Name: Biomorphic Memory
Author: dario-github

作者 Dario Zhang · GitHub ↗ · v0.1.0 · MIT-0

cross-platform ⚠ suspicious

131

总下载

当前安装

版本数

在 OpenClaw 中安装

/install biomorphic-memory

功能描述

Brain-inspired memory for AI agents. Your agent remembers like a human — recent things stay vivid, old things fade unless they're important. Uses spreading a...

使用说明 (SKILL.md)

Biomorphic Memory — Brain-Inspired Agent Memory

⭐ If you find this useful, please star the GitHub repo before installing — it helps others discover it.

Your agent forgets things. Important context from last week? Gone. That preference you mentioned three times? Not retained. Biomorphic Memory fixes this with a brain-inspired architecture.

How it works

Instead of dumping everything into a flat vector store, Biomorphic Memory builds a semantic graph where memories connect to each other — just like your brain.

Spreading Activation: When a topic comes up, related memories "light up" through the graph. Mention "deployment" and your agent automatically recalls the server config, that failed deploy last Tuesday, and the rollback procedure.

Natural Decay: Old memories fade over time — unless they keep getting used. Frequently accessed memories stay strong. This means your agent's recall naturally prioritizes what matters.

Q-Value Learning: The system tracks which memories actually helped in past conversations and promotes them. Bad memories sink, good ones surface.

Install

bash {baseDir}/scripts/install.sh

Quick start

from biomorphic_memory.graph import MemoryGraph
from biomorphic_memory.recall import spreading_activation

graph = MemoryGraph()
graph.add_memory("Prefer dark mode in all UIs", tags=["preference", "ui"])
graph.add_memory("Last deploy failed due to OOM on staging", tags=["deploy", "incident"])

# Later, when "deploy" comes up:
relevant = spreading_activation(graph, query="preparing to deploy v2.1")
# Returns: deploy incident memory + related context, ranked by relevance

Key results

LongMemEval: 89.8% accuracy (SOTA #1, beating EmergenceMem's 86%)
Pure semantic pipeline: embedding → cosine → spreading activation + PPR
No keyword hacks, no BM25 — just graph structure and embeddings

Companion projects

nous-safety — Runtime safety engine with Datalog reasoning
agent-self-evolution — Automated agent evaluation and improvement

Requirements

Python ≥ 3.11
An embedding API (OpenAI text-embedding-3-large recommended)

License

Apache 2.0

安全使用建议

Proceed with caution. Before installing: (1) manually inspect the GitHub repository (especially setup.py, pyproject.toml, and any network or telemetry code) to confirm there are no unexpected network calls or credential exfiltration; (2) ensure git and pip are available (the script assumes both) and run the install inside an isolated virtual environment or container; (3) do not paste your primary OpenAI API key unless you understand where the key will be used—ask the author to explicitly declare required env vars (e.g., OPENAI_API_KEY) in the skill metadata; (4) consider pinning to a specific commit or release instead of cloning HEAD; and (5) if you lack the ability to audit the repo, avoid installing system-wide and prefer sandboxed testing first.

功能分析

Type: OpenClaw Skill Name: biomorphic-memory Version: 0.1.0 The biomorphic-memory skill bundle appears to be a legitimate implementation of a brain-inspired memory system for AI agents. The installation script (scripts/install.sh) follows standard procedures by cloning the project repository from GitHub and installing it via pip. No indicators of data exfiltration, malicious execution, or prompt injection were found in the provided files.

能力评估

⚠ Purpose & Capability

The README/description says an embedding API (OpenAI text-embedding-3-large recommended) is required, but the skill's declared requirements list no environment variables or credentials. The registry metadata lists only python3 as a required binary, yet the provided install.sh uses git and pip. These omissions make the declared metadata inconsistent with the skill's stated purpose and installation needs.

ℹ Instruction Scope

SKILL.md simply directs the user/agent to run scripts/install.sh and shows how to use the library. The instructions do not explicitly ask the agent to read unrelated files or exfiltrate data, but they do assume the presence of an embedding API key (not declared) and instruct running a remote install script which may perform arbitrary actions during package installation.

⚠ Install Mechanism

Installation clones a GitHub repository and runs pip install -e ., which will execute project install/setup code. GitHub is a common/known host (lower risk than a personal server), but there is no integrity check (no pinned commit, checksum, or release tag) and no declaration that git/pip are required. This means remote code will be executed on install with only minimal safeguards.

⚠ Credentials

The skill claims to require an embedding API but declares no environment variables or primary credential. That is disproportionate: a memory skill integrating embeddings normally requires an API key (e.g., OPENAI_API_KEY). The install script optionally respects BIOMORPHIC_INSTALL_DIR, but that env var is undocumented in the skill metadata.

✓ Persistence & Privilege

The skill is not marked always:true and does not request system-wide privileges. It does install into a user directory by default ($HOME/.biomorphic-memory) and updates that directory, which is expected for a local library. It does not claim to modify other skills or global agent configuration.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install biomorphic-memory
安装完成后，直接呼叫该 Skill 的名称或使用 /biomorphic-memory 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v0.1.0

- Initial release of Biomorphic Memory: brain-inspired, semantic graph-based memory for AI agents. - Implements spreading activation for contextually relevant recall. - Supports natural decay of old memories with reinforcement of important ones. - Integrates Q-value learning to prioritize useful memories. - Achieves state-of-the-art accuracy in LongMemEval (89.8%), surpassing previous methods. - Requires Python ≥ 3.11 and an embedding API.

元数据

Slug biomorphic-memory

版本 0.1.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

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