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Analyze location properly: fix projections and geocoding, model real drive-time reach, and map it without misleading anyone.
Complete skill package instant downloadoskari-geospatial-data-analyst.md
Connect your AI once and every skill, prompt and agent loads when you ask. Unlimited also includes the AI CRM your Claude or ChatGPT can run.
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Questions before you buy? A person answers, usually the same day: hello@kissmyskills.com
// the file itself
The first lines of the file your AI will read, exactly as delivered. Nothing rewritten for the page.
You are Oskari, a Senior Geospatial Data Analyst who checks the projection first, because a bad CRS lets the map render while the numbers sit tens of percent out. You have been activated to make location a dimension the user can trust.
// what's inside
Retail, logistics and operations teams making site and coverage decisions off straight-line radius circles.
// two ways to get it
$7 one payment, yours forever
$9/mo cancel anytime, or $59 a year
Subscribers can still buy single files and keep them after they cancel.
// ask your assistant
Go to kissmyskills.com/pages/for-ai-agents and set up the "Oskari - Geospatial Data Analyst AI Skill" skill (handle: oskari-geospatial-data-analyst) for me
Paste it into Claude, ChatGPT, Claude Code, Cursor or Codex. Your AI walks you through connecting KissMySkills (about 3 minutes, 7-day free trial) and loads the skill. What your AI will read →
Drop Oskari into Claude and get a geospatial analyst who replaces the radius circle with a real drive-time isochrone and watches half the business case disappear.
Oskari treats location as a first-class dimension: coordinate reference systems and projections and the quiet errors from getting them wrong; vector and raster data models; PostGIS, GeoPandas and warehouse-native geospatial functions; spatial joins, buffers, isochrones and drive-time analysis; geocoding and address normalization quality; spatial indexing with R-tree, H3, S2 and geohash and grid systems for aggregation; spatial statistics including spatial autocorrelation, Moran's I, hotspot analysis and the basics of kriging; trade-area and site-selection analysis; routing and network analysis; cartographic choices that mislead, such as unnormalized choropleths and bad binning; and the privacy risk in fine-grained location data.
What you get
How to install
Download the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Oskari builds the answer. Includes a full worked example so you see exactly what you get.
After checkout, the download link lands in your inbox. Save the file anywhere on your device.
Claude, ChatGPT, Gemini, Grok, or Copilot - whichever one you already use.
Drop it into the system prompt, Project instructions, or custom instructions field.
Your AI is now configured as a specialist. Ask it anything inside its domain.
No technical knowledge required.
With Unlimited there is nothing to download. Connect your AI once, then just ask: "Load Oskari from KissMySkills."
Analyze location properly: fix projections and geocoding, model real drive-time reach, and map it without misleading anyone. Load it once into Claude Projects and you get a configured Geospatial Data Analyst without re-explaining context at the start of every session. Check every number against a known-good source and an honest holdout before anyone builds a decision on it, and state the uncertainty instead of shipping a single confident point estimate.
Download the .skill package (it contains SKILL.md), paste the contents into Claude Projects Instructions or your AI's system prompt, add your own context and start your first session. Works with Claude, ChatGPT, or any AI chat that accepts system prompts.
Works with Claude (recommended), ChatGPT, Gemini, Perplexity and Copilot, and any AI chat that accepts system prompts. Claude Projects gives the best results.
Without a skill file your AI starts every session as a general assistant. With Oskari loaded it applies Geospatial Data Analyst methodology from the first message, with consistent quality every time. Check every number against a known-good source and an honest holdout before anyone builds a decision on it, and state the uncertainty instead of shipping a single confident point estimate.