Generate weekly AEON skill adoption rankings across configured GitHub forks.
npx skills add https://github.com/anajuliabit/aeon --skill skill-leaderboard
Please help me install this Agent Skill. Skill: skill-leaderboard Source: https://github.com/anajuliabit/aeon/tree/main/skills/skill-leaderboard Command: npx skills add https://github.com/anajuliabit/aeon --skill skill-leaderboard
This Skill turns noisy skill usage across forks into actionable weekly insight, so maintainers learn which skills are genuinely adopted versus just inherited defaults.
aeon.yml meaningfully diverges from upstream defaults, avoiding “heartbeat tautology.”aeon.yml overrides, tracks week-over-week deltas, and writes a dated article plus a notification when meaningful.Run the leaderboard scan for your target repo by setting var to the GitHub owner/repo string (or leave it empty to read the first entry from memory/watched-repos.md).
High-intent search queries and answers about installing and using this skill.
Track skill adoption across GitHub forks by enumerating active forks and inspecting each fork's aeon.yml overrides against upstream defaults. This generates a weekly ranked leaderboard of genuinely adopted skills, filtering out inherited heartbeat configurations.
Fleet monitoring for autonomous agents tracks recurring behavior changes across configured repositories using week-over-week state comparison. It reads memory state files to compare enabled states, model overrides, var usage, and scheduling changes to identify emergent preferences.
Generate a ranked weekly report by setting the target GitHub owner/repo string or reading from watched-repos memory, then applying configured-tier classification to active forks. The scan outputs a dated article and notification gated by a minimum configured-fork denominator.
Yes, the skill leaderboard requires a minimum configured-fork denominator before generating article or notification outputs. This threshold ensures reporting only occurs when enough forks meaningfully diverge from upstream defaults to provide statistically useful adoption data.
Monitor aeon.yml configuration diffs across active forks to produce evidence-based Promote, Match, Sunset, and Fleet-only recommendation categories. This classification relies on enabled and override patterns observed exclusively within the configured fleet.
Fork adoption metrics show high default usage because unconfigured forks inherit upstream aeon.yml settings, creating heartbeat tautology. The leaderboard solves this by ranking adoption only among forks whose configurations meaningfully diverge from upstream defaults.
anajuliabitCompare fork aeon.yml configurations against upstream AEON skill defaults.
aaronjmarsCompute weekly Aeon skill adoption leaderboards across configured GitHub forks.
anajuliabitSynthesize fork-cohort, release, and contributor data into a weekly fleet-state digest.
aaronjmarsCollect daily GitHub star and fork activity data for repositories.