Weekly ranking of which skills are most popular across all active forks
Today is ${today}. Generate a leaderboard of the most popular Aeon skills across all active forks.
Determine the target repo. If ${var} is set, use that. Otherwise read memory/watched-repos.md and use the first watched repo. Store as TARGET_REPO.
Fetch all active forks (pushed within the last 30 days):
CUTOFF=$(date -u -d "30 days ago" +%Y-%m-%dT%H:%M:%SZ 2>/dev/null || date -u -v-30d +%Y-%m-%dT%H:%M:%SZ)
gh api repos/${TARGET_REPO}/forks --paginate --jq "[.[] | select(.pushed_at > \"$CUTOFF\") | {owner: .owner.login, full_name: .full_name, pushed_at}]"
If no active forks found, log "SKILL_LEADERBOARD_NO_FORKS" and stop (no notification).
Read each active fork's aeon.yml to extract enabled skills:
gh api repos/{fork_full_name}/contents/aeon.yml --jq '.content' | base64 -d
For each fork, extract all skill entries where enabled: true. If the fork has no aeon.yml or the API returns 404, skip it and note "no aeon.yml".
Aggregate skill counts across all forks:
enabled: true in any fork, count how many forks have it enabled.aeon.yml.Compare to last week's leaderboard — check for articles/skill-leaderboard-*.md files from the last 7 days. If one exists, extract its ranked list and compute week-over-week changes (new entries, rank changes, dropouts).
Identify insight categories:
Write the leaderboard article to articles/skill-leaderboard-${today}.md:
# Skill Leaderboard — ${today}
*${N} active forks scanned (pushed in last 30 days)*
## Top Skills Across the Fleet
| Rank | Skill | Forks Enabled | % of Fleet | Change |
|------|-------|---------------|------------|--------|
| 1 | skill-name | N | XX% | — |
| 2 | skill-name | N | XX% | ↑2 |
| ... | ... | ... | ... | ... |
## Consensus Skills (>50% of forks)
[List skills with broad adoption and why they matter]
## Adoption Gaps
[Skills with zero fork enables — these may need better docs or examples]
## Week-over-Week
[Changes from last week's leaderboard, or "First leaderboard — no prior data" if this is the first run]
## Fleet Summary
- **Active forks scanned:** N
- **Total skill slots enabled (across all forks):** N
- **Unique skills seen:** N
- **Forks with no aeon.yml:** N (likely template/non-running forks)
---
*Source: GitHub API — forks of ${TARGET_REPO}*
Send notification via ./notify:
*Skill Leaderboard — ${today}*
Top skills across ${N} active forks:
1. [skill] — N forks (XX%)
2. [skill] — N forks (XX%)
3. [skill] — N forks (XX%)
4. [skill] — N forks (XX%)
5. [skill] — N forks (XX%)
Consensus: [list of skills enabled by >50% of forks, or "none yet"]
Adoption gaps: [skills with zero fork enables]
Full leaderboard: articles/skill-leaderboard-${today}.md
Only send a notification if at least 2 active forks were found with readable aeon.yml files. Otherwise log "SKILL_LEADERBOARD_INSUFFICIENT_DATA" and stop.
Log to memory/logs/${today}.md:
## Skill Leaderboard
- **Forks scanned:** N active (of M total)
- **Top skill:** [skill-name] (N forks)
- **Consensus skills:** [list or "none"]
- **Notification sent:** yes/no