Find app ideas

• The user has no idea yet, or a broad area ("health", "something for teachers").
• The user has an idea and wants to know if there is demand and room ("validate a habit tracker for ADHD").
• Not for improving an existing app (use app-audit-lite or aso-keywords-metadata-rewrite).

• niche (optional): a seed area or idea, e.g. habit tracker, plant care, finance for couples. Without it, start from the charts (step 1).
• store (optional, default apple): apple or play. Run once per store; demand differs.
• country (optional, default us).

Ask at most one question before starting: whether the user has constraints (solo dev, no backend, paid vs free). Otherwise assume a solo developer shipping in 4–8 weeks.

Costs in AppGoat credits; watch the footer of each tool result. Without the MCP, use the REST equivalents in the REST calls below.

1. Seeds.
   • With niche: write 8–10 seed terms a user would type into the store (2–3 words, no brand names).
   • Without niche: get_charts {store, country, chart: "free", category} and {chart: "grossing"} for 4 categories (Apple genre ids: 6013 Health & Fitness, 6007 Productivity, 6017 Education, 6012 Lifestyle; Play: HEALTH_AND_FITNESS, PRODUCTIVITY, EDUCATION, LIFESTYLE) - 8 calls, 8 credits. Take apps with is_new or delta ≥ 10 and the grossing apps outside the top 20 free; derive 8–10 seed terms from what they do.
2. Expand. keyword_research {terms: 5 seeds, store, country, include: ["related", "suggestions"]}, twice for 10 seeds - 5 per seed, 50 credits. Collect related terms and suggestions.
3. Measure candidates. Pick the 25 most specific candidate terms (prefer 2–4 words that describe a job, e.g. "adhd planner", not "planner"). keyword_research {terms: 25 terms, store, country, include: ["top_apps"]} - 1 per keyword, 25 credits. Terms that come back pending are being measured: call again with just those after a minute (charged again only for those).
4. Check supply. For the 8 best terms by the demand rule below: get_app {app: <app_id>, store, country} for the top 3 top_apps of each - ~24 credits - to read updated_at, rating, ratings_count, price, has_iap. Optionally search_apps {q: term, store, limit: 20} - 1 each - to count how many apps target it directly by title.
5. Find the wedge. For the 5 best niches: get_reviews {app: <top incumbent>, store, country, rating: "1-2", limit: 100} for the top 2 incumbents - ~10 credits. Group complaints into themes.
6. Rank and write up (no calls).

Budget: about 150–200 credits per run (up to ~250 with refreshes and re-measured pending terms). Stop early if credits_remaining falls below the remaining budget and tell the user.

• Demand: popularity ≥ 30 (5–100 scale). Popularity ≥ 50 with difficulty ≥ 70 is a "big but crowded" market: keep it only if supply is weak.
• Difficulty: ≤ 55 to be a candidate; ≤ 35 is "easy".
• Weak supply (at least one must hold):
  • median rating of the top 10 < 4.3, or
  • ≥ 3 of the top 10 not updated in 12 months, or
  • ≤ 2 of the top 10 have the term (or a close variant) in their title, or
  • the top 3 average < 5,000 ratings (Apple) / < 100k installs (Play).
• Monetization signal: at least one top-10 app has IAP or is paid, or the term's apps appear in the grossing chart. Without it, label the idea "hobby / growth only".
• Opportunity score (rank by it): popularity × (1 − difficulty/100) × supply_weakness, where supply_weakness = 1 + 0.25 per weak-supply condition met (max 2).
• Wedge: a pick needs a complaint theme mentioned in ≥ 5 of the incumbents' 1–2★ reviews, or a missing feature named in ≥ 3. No wedge: drop it to the "watch" list.
• Exclude: regulated or high-liability niches (medical diagnosis, lending, gambling), anything that depends on another company's private API, and terms that are mostly a brand name.
• Return 3–5 picks. If fewer qualify, say so and show the near misses with the rule they failed.

# App ideas: <niche or "chart scan"> (<store>, <country>) - <date>

| # | Idea | Key term | Popularity | Difficulty | Top-10 median ★ | Stale incumbents | Score |
|---|---|---|---|---|---|---|---|
| 1 | ADHD-friendly habit tracker | adhd habit tracker | 41 | 28 | 4.1 | 4 of 10 | 39.4 |

## 1. <Idea>
- **Demand:** <term> (pop 41), <term 2> (pop 33), related: <terms>
- **Supply:** top apps <name (4.0★, updated 2024-11)>, …; only 1 of 10 has the term in its title.
- **Wedge:** users complain about <theme> ("<≤ 120-char quote>", 2★) and <theme>.
- **Money:** <who charges what>.
- **MVP in one line:** <scope a solo dev can ship in 4-8 weeks>.
- **Launch keywords:** title "<≤ 30 chars>", subtitle "<≤ 30 chars>".

## Near misses
- <term>: popularity 58 but difficulty 81 and top apps average 4.7★.

_Credits used: <sum of the footers>._

**Automate this →** re-run monthly to see new movers; once you pick one, track its keywords with
`track_keywords` and run `aso-keywords-metadata-rewrite` before launch.

Without the AppGoat MCP server, call the API directly. Base URL https://api.appgoat.ai/v1, header x-api-key: $APPGOAT_API_KEY (create a key at https://dash.appgoat.ai). Responses are { "data": …, "meta": { "credits_used", "credits_remaining", … } }; errors carry error.hint.

curl -s -G -H "x-api-key: $APPGOAT_API_KEY" https://api.appgoat.ai/v1/keywords \
  --data-urlencode "qs=habit tracker,adhd planner" -d store=apple -d country=us -d include=top_apps