القائمة
Generate a MapRoulette challenge from scan results for defect classes with high false-positive rates. Creates GeoJSON tasks constrained to MetroNow zone polygons.
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
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.
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.
Unified code review and audit standards for the MetroNow Atlas TIGER Audit Console (https://github.com/AICincy/MetroNow.git). Use this skill when auditing any code in the MetroNow project, doing a PR review, checking code quality, validating accessibility, reviewing Docker config, or when someone asks "review this code," "audit the frontend," "check my PR," "what's wrong with this file," or "does this meet our standards." The codebase is vanilla JavaScript (IIFE pattern, no framework), single-file HTML with inline CSS/JS, IBM Plex typography, Leaflet maps, and an Express.js backend on port 3000 that shells out to the Python `osm` CLI. Covers JS, HTML, CSS, and Dockerfile review with severity-classified findings.
| name | maproulette-challenge |
| description | Generate a MapRoulette challenge from scan results for defect classes with high false-positive rates. Creates GeoJSON tasks constrained to MetroNow zone polygons. |
| when_to_use | User mentions MapRoulette, crowdsource review, needs human review for defects, or discusses Class B defects that need manual verification |
| allowed-tools | Read Grep Glob Bash(python *) Bash(curl *) |
| argument-hint | [zone] [defect-class] |
| arguments | ["zone","defect_class"] |
Generate a MapRoulette challenge for $defect_class defects in $zone.
Per RESEARCH-FINDINGS.md Item 17 and the OSM Automated Edits code of conduct: corrections with >5% expected false-positive rate must go through MapRoulette rather than direct API edits. This includes:
!p="osm-audit-$zone/scan-results.json"; if [ -f "$p" ]; then python -c "import json; d=json.load(open('$p')); s=d['summary_stats']; print(f'Total: {s[\"total\"]}, AB: {s[\"class_ab_count\"]}, A: {s[\"class_a_count\"]}, B ways: {s[\"class_b_way_count\"]}, Gaps: {s[\"gaps_found\"]}')"; else echo "No scan results found. Run /zone-audit first."; fi
Create Project — POST to https://maproulette.org/api/v2/project
MetroNow TIGER Audit — {zone_name}Create Challenge — POST to https://maproulette.org/api/v2/challenge
src/osm/zones/__init__.py (the ZONES dict)tiger, metronow, hamilton-countyBatch Tasks — POST GeoJSON features as tasks
mr-cli for cooperative challenges with task attachments