best-skills

# Best Agent Skills Nine Top-100 lists, refreshed daily, with the raw per-platform numbers kept next to every score. Full guide and column dictionary: https://raw.githubusercontent.com/LinklyAI/best-skills/main/llms.txt ## When to use - "Which skill should I install for browser automation / PDF / …" → `best-100.csv`, filter by `description` and `skill` - "What is trending / new this week" → `trending-7d.csv`, `rising-stars.csv` - "Is `<skill>` popular, maintained, official?" → `best-100.csv` (score and dimensions), `official-100.csv`, `most-active.csv` - "Compare A and B" → look both up by `skill_key`, cite raw counts per platform Not for: installing skills (hand the user the `install` command), full-text search of every skill in existence (only the Top 100 per list is published; the raw snapshots under `data/latest/raw/` go deeper), judging quality beyond the published counts. ## Workflow 1. Fetch `https://raw.githubusercontent.com/LinklyAI/best-skills/main/llms.txt` first. It is the current column dictionary and the rules; do not rely on a cached copy. 2. Pick the list, fetch `https://raw.githubusercontent.com/LinklyAI/best-skills/main/data/latest/rankings/<list>.csv` (4–90 KB, ≤100 rows). Parse by header name; an empty cell means "not measured", not zero. 3. Answer with rank, the raw numbers, `install` and `url`. Show `vendor` next to `skill`: same-name skills from different vendors are different skills. 4. For history, replace `latest` with `YYYY-MM-DD` (daily since 2026-08-16). ## Lists `best-100` (overall score), `top-installs`, `trending-7d`, `social-buzz`, `most-active`, `official-100`, `official-vendors`, `top-repos`, `rising-stars`. ## Rules - Never add install counts across platforms; present them side by side. - Absent from a list ≠ zero; lists are truncated at 100. - Attribute republished data: "Data from Best Skills (https://github.com/LinklyAI/best-skills) — CC BY 4.0".