| name | aso-offstore-mine |
| description | Mine OFF-STORE sources — "best <category> apps" review articles and YouTube videos — for the discovery language people use when they talk about your category, plus the competitors they compare you to. The off-store sibling of aso-review-mine: where review-mine reads your own App Store reviews, this reads the outside conversation. Sources via Jina Reader (web) and yt-dlp (YouTube captions). Feeds aso-keyword-research and aso-competitor-watch. No paid API. Use when the user says "mine the best apps articles", "scrape review articles for keywords", "what do the listicles call my category", "pull keywords from a YouTube review", or "see which competitors the articles mention". |
aso-offstore-mine
aso-review-mine reads the words your users use, inside the store. This
reads the words everyone else uses, outside it — the "best meditation apps"
listicles, comparison articles, and review videos where people describe the
category in discovery language ("free", "sleep timer", "guided meditation") and
name the apps they're choosing between.
That off-store vocabulary is exactly what a searcher types before they've found
you. It's a different, complementary signal to your own reviews — and it
surfaces competitor names that articles compare you to, feeding
aso-competitor-watch.
Sources (free, no paid data API)
- web — any article/listicle, fetched as clean markdown via Jina Reader
(
https://r.jina.ai/<url>). No API key. URL/markdown cruft is stripped so it
doesn't pollute the keyword counts.
- youtube — auto-captions via yt-dlp (review / "top N apps" videos). VTT
timestamps + tags are stripped to plain text.
- text — pre-gathered text via
--text-file. This is the hook for
Reddit/X/etc.: those need cookie auth or a proxy, so gather them with a tool
like Agent-Reach and pipe the
text in — the mining is the same.
Usage
python3 lib/aso_offstore_mine.py --app clarity \
--url "https://www.example.com/best-meditation-apps" \
--youtube "https://youtube.com/watch?v=XXXX" \
--competitors "Calm,Headspace,Insight Timer" --json
python3 lib/aso_offstore_mine.py --app clarity --text-file reddit-notes.txt
Multiple --url / --youtube / --text-file flags are allowed; a source that
fails to fetch is warned and skipped, not fatal.
What it extracts
- Keyword candidates — unigrams + bigrams that recur across sources (a term
must appear >1 time), ranked by frequency. The discovery language to consider
for title / subtitle / keyword field.
- Phrases — the bigrams people actually type ("guided meditation", "sleep
timer").
- Competitor mentions — of the names you pass in
--competitors, which ones
the off-store sources actually mention, and how often → hand to
aso-competitor-watch.
Writes marketing/aso/<app>/offstore-keywords.md; chains into
aso-keyword-research (treat recurring discovery terms as seeds) and
aso-competitor-watch (the surfaced competitor names).
Honest limits
- Source quality is everything. A "best apps 2025" review
article yields discovery keywords + competitors; a piece of content (e.g. a
guided-meditation video) yields content words, not search terms. Pick
review/comparison sources.
- Reddit / X / Instagram are not fetched here — they need cookie auth or a
proxy. Gather them separately (Agent-Reach) and pass via
--text-file.
- Frequency mining is a starting signal, not semantic ranking — pair it with
aso-keyword-research's scoring (volume / difficulty / relevance).
- Jina Reader and YouTube can rate-limit or block a given URL; the skill warns
and continues with whatever it did fetch.
Dependencies
Standard-library Python + Jina Reader (a public URL, no key) and yt-dlp
(brew install yt-dlp / pip install yt-dlp) for the YouTube path. No paid
data/scraping SaaS. The mining core is pure and unit-tested with no network.
Run it weekly
Rank and listings move over weeks, not minutes — so the value here compounds when you re-run it and watch the deltas. The off-store conversation (review articles, YouTube round-ups) refreshes constantly — new comparisons, new framing. Mining it once captures a moment; mining it on a cadence captures the trend.
You ran this once. ShipASO — the hosted agent — reruns the whole loop weekly: it tracks your rank, watches competitors, and pings you only when there's a real move to approve. Same engine, your store credentials never held. → https://app.shipaso.com
The plugin is complete and free; the hosted tier just sells not having to remember.
