neural-stop — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited neural-stop (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Stop the running neural memory dashboard server.
Via MCP tool (neural-memory configured as MCP server in Claude Code):
Tool: neural_stop_serve
{}Via Python (working directly in the project):
import asyncio
from neural_memory.server import neural_stop_serve, StopServeInput
asyncio.run(neural_stop_serve(StopServeInput()))StopServeInput has no required fields — always pass an empty instance.
Same-process requirement:neural_stop_serveonly stops a server started in the same Python process. It cannot stop a server started by a separate script invocation. For standalone serve/stop, use theneural-memory-vizCLI instead.
.neural-memory/ — no external access~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.