القائمة
Cross-reference OSM data against CAGIS quarterly road centerlines and ODOT TIMS Road Inventory for ground-truth validation of defect classifications.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | cagis-conflate |
| description | Cross-reference OSM data against CAGIS quarterly road centerlines and ODOT TIMS Road Inventory for ground-truth validation of defect classifications. |
| when_to_use | User mentions CAGIS, ODOT, ground truth, cross-reference, validate classification, compare centerlines, or check highway type |
| allowed-tools | Read Grep Glob Bash(python *) Bash(curl *) |
| argument-hint | [zone or way-id] |
| arguments | ["target"] |
Cross-reference OSM against authoritative sources for: $target
data-cagisportal.opendata.arcgis.comsource= changeset tagtims.dot.state.oh.ushttps://tiles.mblaine.com/ohio/{z}/{x}/{y}.png (mblaine's Mapnik render of ODOT data)gis.dot.state.oh.us
paths. Until a working endpoint is wired in src/osm/, do NOT include
"ODOT TIMS" in the source= tag of any submitted changeset.tl_2024_39061_roads.zip (Census Bureau, FIPS 39061 = Hamilton County)highway=residential but CAGIS says connector/arterialThe 2007 TIGER import mapped CFCC A4x codes to highway=residential by default (RESEARCH-FINDINGS Item 3). Many should be:
highway=unclassified (rural connectors)highway=tertiary (suburban arterials)highway=service (driveways/alleys)CAGIS and ODOT TIMS are the authoritative sources to determine the correct classification.
Every changeset that uses CAGIS data must include:
source=CAGIS Open Data Hub (data-cagisportal.opendata.arcgis.com)
with the required disclaimer and data creator credit per CAGIS terms.
Run the full TIGER defect audit pipeline for a MetroNow service zone — fetch from Overpass, classify defects, analyze history, generate reports.
Diff OSM geometry and attributes against TIGER/Line 2024 to identify import drift, new roads, and name-field artifacts in MetroNow zones.
Generate a MapRoulette challenge from scan results for defect classes with high false-positive rates. Creates GeoJSON tasks constrained to MetroNow zone polygons.
Deep revision history analysis for specific OSM ways — fetches full version history from OSM API v0.6, identifies import bot vs human edits, classifies review status with confidence scores.
Submit corrections to OSM API v0.6 with full community compliance — proper changeset tags, size limits, rate-limit awareness, and dry-run support.
Decompress MetroNow docs so future-you (and fresh AI sessions) can pick the project back up cold without re-deriving everything. Use when the user says docs are confusing, plain, dense, hard to follow, missing context, jargon-heavy, jump straight to conclusions, or are hard to come back to after time away; asks why something is the way it is; says they can't tell what a term means; asks for a walkthrough, explainer, primer, or context refresher; says a section assumes too much; or wants visual aids. Diagnoses missing-middle gaps (undefined jargon, unstated WHY, skipped bridge steps, prose where a picture is needed) and rewrites sections using a fixed template — definition first, then bridge steps, then a load-bearing diagram, then code citations. Outputs to docs/explainers/<topic>.md or in-place edits. No VitePress, no static-site generator — just markdown that GitHub renders.