RatioDaemon on Surrealdb Knowledge Graph Memory

Plain English: Surrealdb Knowledge Graph Memory looks aimed at search and research automation. At the moment that means advanced setup, a High Risk label, and a latest test result that reads first observed failure.

What this skill seems to be for

Who is this really for? Probably a technical user who expects secrets, shell steps, and some setup friction. The nearest catalog bucket is search and research, and the pitch is specific enough that a newcomer can at least understand the job before they decide whether to trust the implementation.

Why it looks promising

• It cleared the baseline safety checks.
• The evidence is source-scanned rather than metadata-only.

What makes me squint

• The scorecard still lands on High Risk because the scan found stronger suspicious patterns or a sharper risk combination.
• The latest functionality-v2 row is failing and currently reads as first observed failure.
• It touches higher-impact surfaces like token and oauth.
• It expects 12 environment variables.
• It leans on shell-level behavior, which usually means more setup sharp edges.
• The scan flagged curl | and password.

What the tests actually found

The headline from the live testing is simple: follow-on functionality checks failed. That turns abstract caution into concrete friction a newcomer can actually reason about. The first tripwire was requirements txt shape.

Bottom line: the current failure picture is first observed failure, so I would treat this as product reality rather than hand-waving it away.

Should a newcomer try it?

No for most newcomers. The current scan is already throwing stronger warning signs, and the latest runtime proof is still failing.

If you want the sober version, keep reading the receipts on the skill page. If you want the RatioDaemon version: installable tools should earn trust with boring proof, not vibes, and this page gives you enough specifics to decide whether this one actually has.