@dennis-da-menace

Agent Memory

Persistent memory for AI agents to store facts, learn from actions, recall information, and track entities across sessions.

Current version
v1.0.0
26 2.4万All installs 419

README.md

text/markdown · 5617 bytes

SKILL.md

text/markdown · 1385 bytes

cli/entity.py

text/plain · 3626 bytes

cli/fact.py

text/plain · 3462 bytes

cli/learn.py

text/plain · 2392 bytes

examples/basic_usage.py

text/plain · 2848 bytes

requirements.txt

text/plain · 48 bytes

src/__init__.py

text/plain · 212 bytes

src/memory.py

text/plain · 22097 bytes

tests/test_memory.py

text/plain · 5253 bytes

Security Scan

Status

clean

Open VirusTotal

OpenClaw

gpt-5-mini

clean

OpenClaw analysis

This skill is internally coherent: it implements a local SQLite-backed agent memory (reads/writes ~/.agent-memory/memory.db by default), requires no credentials or external network access, and its files match the SKILL.md usage.

Confidence: high

VirusTotal

Type: OpenClaw Skill Name: agent-memory Version: 1.0.0 The OpenClaw AgentMemory skill bundle is a self-contained, SQLite-based persistent memory system for AI agents. All code and documentation are aligned with its stated purpose of storing facts, lessons, and entities. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, obfuscation, or prompt injection attempts against the analyzing agent. The skill uses standard Python libraries, manages its database in a user-specific directory (`~/.agent-memory/memory.db`), and explicitly states 'No external dependencies' in `requirements.txt`, indicating a low supply chain risk.

Metadata

  • Owner: @dennis-da-menace
  • Created: 2026/01/31
  • Updated: 2026/04/30
  • Versions: 1
  • Comments: 1
  • Scan checked at: 2026/02/11

Runtime

No runtime requirements are exposed in the official public payload.

Agent Memory | ClawHub CN