competitor-scan

/competitor-scan — Category density and ratings

Algorithm

1. Resolve the location: call geocode on the address the user gave, take lat/lon.
2. Resolve the category. If the user gave a 2GIS rubric_id, use it directly with search_by_rubric. If they gave a name ("barbershop", "coffee"), use search_places with that query and type = org instead — there is no rubric lookup tool in this server.
3. Call search_by_rubric (or search_places) with point = "lon,lat" and radius (default 1500). Note the total count — that is the density number.
4. For the top 5 results call get_reviews with each place_id. Record rating and review count.
5. For the two highest-rated call get_place to pull schedule and contacts.
6. Summarize: how many competitors, rating spread, who dominates, where the gap is (low ratings, few reviews, short opening hours).

Response format

## Barbershops within 1.5 km of Arbat 12

**Density**: 23 in radius
**Rating spread**: 3.4 — 4.9 (median 4.3)

| # | Name | Rating | Reviews | Hours |
|---|------|--------|---------|-------|
| 1 | ... | 4.9 | 480 | 10:00–22:00 |

**Gap**: 9 of 23 have under 20 reviews — thin social proof in this radius.

Notes

• Report only what the tools returned. Do not estimate revenue or traffic — 2GIS has no such fields.
• get_reviews accepts an optional limit; keep it small (10) since only the aggregate matters.
• A large total with a small returned page is normal: increase page_size on search_places or paginate before claiming a number is final.

Examples

/competitor-scan barbershop "Arbat 12" 1500
/competitor-scan "coffee shop" 55.7558,37.6173
/competitor-scan pharmacy "Kazan, Bauman 5" 800