Spotlighting Your Project 来源：https://prompts.chat/prompts/githubsponsors14
Create a compelling data-driven section showing the impact of [project name]: downloads, users helped, issues resolved, and community growth statistics.
Checks CSV time series (metrics, sensor readings, sales by hour) for data problems before you chart or alert on them: missing intervals, duplicate or out-of-order timestamps, empty values, flatlines from stuck exporters, robust median/MAD spikes, and counter resets. Use when a dashboard looks wrong, before training a forecast, or when asking "is this data complete?". Includes a stdlib Python checker with --self-test. 来源：https://prompts.chat/prompts/cmvexglly000rjr088nxj0x8r
Turns request counts into SLO answers: SLI, error budget for a 28d or 30d window, budget consumed and remaining, burn rates over 5m to 3d, multiwindow burn-rate alerts (page at 14.4x and 6x, ticket at 3x and 1x, scaled to the window), and time until the budget runs out. Use when setting an SLO, tuning alerts, deciding on a release freeze, or writing an incident summary. Includes a stdlib Python calculator with --self-test. 来源：https://prompts.chat/prompts/cmvgd54l0000ikw08w8549ftc
