openmapstack-skills: AI-agent skill for reproducible, validated GIS analysis

by jaakla · Agent Tool · ★ 76

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install openmapstack-skills

npx skills@1.5.26 add jaakla/openmapstack-skills --skill open-map-stack -g
npx skills@1.5.26 add https://github.com/jaakla/openmapstack-skills/tree/v0.4.0/skills/open-map-stack -a codex -y

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 67/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-skillclaude-codeduckdbgeoparquetgeospatialgismaplibreopen-sourceopenstreetmapoverture

Quick Facts

Stars76
Forks11
LanguageHTML
CategoryAgent Tool
LicenseMIT
Quality Score67/100
Open Issues23
Last Updated2026-10-29
Created2026-05-03
Platformsclaude-code
Est. Tokens~20k

About openmapstack-skills

openmapstack Four complementary skills for geospatial decisions, data discovery, spatial SQL and reproducible analysis projects. Install: OpenMapStack gives your favorite AI agent: Claude Code, Codex, Cursor, OpenCode, PI and 50+ other agents a production workflow from authoritative data discovery through reusable analysis pipeline.py to interactive web and GIS deliverables.

Compatible Skills

These tools work well together with openmapstack-skills for enhanced workflows:

  • mazzap — semantic(0.46)+complementary+rare_topics+same_lang+similar_pop+shared_platform (75%)
  • gdal-mcp — semantic(0.33)+complementary+rare_topics+same_lang+similar_pop+shared_platform (70%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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