signal-over-noise

signal-over-noise is an Observability & incident response skill for AI agents, published by atlanhq in the application-sdk repository on GitHub. Skillspace rates signal-over-noise F (52/100) and it passed the safety scan; the rating is based on static analysis only.

Good investigations depend on good signals. Use this skill to improve the quality of observability in a Python codebase — surfacing failures that are currently hidden, and removing noise that buries the signals you need. Errors swallowed silently, stack traces discarded, log output that can't be queried, credentials leaking into logs, INFO-level chatter drowning out what matters: all of these slow down debugging and erode trust in your observability stack. Standardising log levels means DEBUG stays out of production, INFO marks genuine lifecycle events, and ERROR only fires when something actually failed — so when you filter to WARNING or above during an incident, you see exactly what you need and nothing you don't. Run this before an incident review, before onboarding a service, or any time investigations feel harder than they should.

Grade

F

Quality

52 / 100

Safety

Passed

GitHub stars

27

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

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