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Postgis query patterns

Skill buildmoonshot/skillpacks/skills/gis/intermediate/postgis-query-patterns

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Install
npx -y skills add buildmoonshot/skillpacks --skill postgis-query-patterns

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Use when writing PostGIS or spatial SQL — distance, proximity, intersection, or geometry storage queries. Makes the agent use correct SRIDs, spatial indexes, and the right ST_ functions, so spatial SQL is both correct and fast instead of silently slow or wrong.

SKILL.md

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PostGIS Query Patterns

PostGIS rewards correct spatial SQL and quietly punishes the rest with wrong answers or full table scans. Follow the patterns.

Storage & SRID

  • Store geometry with a known SRID (typmod like geometry(Point, 4326) or ST_SetSRID). Operations between different SRIDs error or mislead — ST_Transform to align.
  • Choose geography for accurate distances over large/global areas (meters on a sphere); geometry in an appropriate projected CRS for fast planar math.

Make queries use the index

  • Put a GiST index on every geometry column you query.
  • Use index-assisted operators/functions: &&, ST_Intersects, ST_DWithin. These hit the index.
  • Avoid ST_Distance(a, b) < x in a WHERE clause — it can't use the index and forces a full scan. Use ST_DWithin(a, b, x) instead.

Correctness gotchas

  • && is bounding-box only — fast but approximate. Use it as a prefilter, then ST_Intersects for the exact test.
  • Validate geometry before overlays (ST_IsValid / ST_MakeValid) — see validate-geometry.
  • ST_DWithin distance units follow the type: meters for geography, CRS units for geometry (degrees if you left it in 4326 — usually not what you want for a distance).

Why this matters

Spatial SQL fails quietly in two directions: wrong SRID or wrong function gives a confident wrong answer, and a missing index turns a sub-second query into a minutes-long table scan that still "works" in testing and falls over in production. The patterns above keep queries both correct and fast.

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