Spatial Join Sanity
Use when performing a spatial join or location-based filter between two layers — joining attributes by location, or selecting features that intersect, contain, or fall within another layer. Makes the agent pick the correct spatial predicate, confirm CRS and geometry preconditions, and handle one-to-many matches deliberately instead of silently inflating or dropping records.
Install
$ agentstack add skill-buildmoonshot-skillpacks-spatial-join-sanity ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-buildmoonshot-skillpacks-spatial-join-sanity) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
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How agent discovery & health will work →About
Spatial Join Sanity
A spatial join is where CRS bugs, geometry bugs, and cardinality bugs all converge. Do it deliberately.
Before the join
- Confirm both layers share a CRS (see
crs-discipline) and have valid geometry (seevalidate-geometry). A spatial join across mismatched CRSs returns wrong matches with no error.
- Pick the predicate that matches the question. Don't default to "intersects" for everything:
- points-in-polygons →
within/contains - any overlap →
intersects - shared boundary / adjacency →
touches - "near, within N meters" → a distance predicate (
ST_DWithin,near) — not intersects, and not a post-hoc distance filter.
Handle cardinality on purpose
A spatial join is one-to-many. A point on a shared border matches both polygons; overlapping polygons multiply rows. Decide explicitly:
- keep all matches, or
- keep the largest-overlap / nearest / first match.
Don't let the join silently change your record count.
Sanity-check the result
Compare input vs output row counts and state it. If a 10,000-point layer becomes 14,000 rows after a join to polygons, that's a boundary/overlap multiplication that needs an explanation — not something to hand over unnoticed. A point count that drops means unmatched features fell out of an inner join; decide whether that's intended.
Why this matters
Spatial joins produce a table that looks normal whether or not it's correct. The errors — wrong predicate, CRS mismatch, silent row multiplication — don't surface as crashes; they surface as a deliverable with the wrong counts. A predicate chosen on purpose and a row-count check catch them before they ship.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: buildmoonshot
- Source: buildmoonshot/skillpacks
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.