Favorites Curator

Maintain a file-backed catalog of useful local resources.

Do First

1. 1. Run scripts/scan_favorites.py to refresh entries and the latest snapshot.
2. Run scripts/daily_digest.py to compare the latest snapshot with the previous one and produce a digest.
3. Run scripts/notify_candidates.py when the user wants short notification copy for notable items.

Paths

• - Entries: INLINECODE3
• Snapshots: INLINECODE4
• Reports: INLINECODE5
• Cache: INLINECODE6
• Skill code: INLINECODE7
• Naming and schema notes: INLINECODE8

Covered Sources

• - ~/ai git repositories
• INLINECODE10 installed formulae and casks
• INLINECODE11 and INLINECODE12
• INLINECODE13
• INLINECODE14
• INLINECODE15
• INLINECODE16
• INLINECODE17
• INLINECODE18

Expected Workflow

Refresh catalog

CODEBLOCK0

Use --limit-source to iterate on one source:

CODEBLOCK1

Generate daily digest

CODEBLOCK2

This produces a Markdown report with:

• - new entries
• updated entries
• likely similar items worth deduping or cross-referencing
• notable items worth surfacing

Emit notification copy

CODEBLOCK3

Use --top N to cap the number of lines.

Data Rules

• - Prefer local metadata over online enrichment.
• Leave missing fields empty or mark them as inferred in field_sources.
• Keep filenames ASCII, sortable, and machine-friendly.
• Store one entry per file.
• Update the same entry file on re-scan instead of creating duplicates.

Output Contract

Each entry file must keep these fields in frontmatter:

• - INLINECODE22
• INLINECODE23
• INLINECODE24
• INLINECODE25
• INLINECODE26
• INLINECODE27
• INLINECODE28
• INLINECODE29
• INLINECODE30

Other helper fields are allowed when useful for automation.

Notes

• - The scripts are local-first and safe to run repeatedly.
• INLINECODE31 is used once per scan; avoid tight cron loops.
• Read references/naming-and-model.md before changing filename rules or schema.