Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add curiositech/some_claude_skills --skill geospatial-data-pipelinegit clone --depth 1 https://github.com/curiositech/some_claude_skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/curiositech/some_claude_skills/geospatial-data-pipeline)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/geospatial-data-pipeline"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/geospatial-data-pipeline/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/geospatial-data-pipeline"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/geospatial-data-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 259 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00089 | $0.03259 |
| Opus 5 | $0.00044 | $0.01630 |
| Sonnet 5 | $0.00018 | $0.00652 |
| Haiku 4.5 | $0.00009 | $0.00326 |
Grade A, and why
geospatial-data-pipeline scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 408 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Geospatial Data Pipeline
Expert in processing, optimizing, and visualizing geospatial data at scale.
When to Use
✅ Use for:
- Drone imagery processing and annotation
- GPS track analysis and visualization
- Location-based search (find nearby X)
- Map tile generation for web/mobile
- Coordinate system transformations
- Geofencing and spatial queries
- GeoJSON optimization for web
❌ NOT for:
- Simple address validation (use address APIs)
- Basic distance calculations (use Haversine formula)
- Static map embeds (use Mapbox Static API)
- Geocoding (use Nominatim or Google Geocoding API)
Technology Selection
Database: PostGIS vs MongoDB Geospatial
| Feature | PostGIS | MongoDB |
|---|---|---|
| Spatial indexes | GiST, SP-GiST | 2dsphere |
| Query language | SQL + spatial functions | Aggregation pipeline |
| Geometry types | 20+ (full OGC support) | Basic (Point, Line, Polygon) |
| Coordinate systems | 6000+ via EPSG | WGS84 only |
| Performance (10M points) | <100ms | <200ms |
| Best for | Complex spatial analysis | Document-centric apps |
Timeline:
- 2005: PostGIS 1.0 released
- 2012: MongoDB adds geospatial indexes
- 2020: PostGIS 3.0 with improved performance
- 2024: PostGIS remains gold standard for GIS workloads
Common Anti-Patterns
Anti-Pattern 1: Storing Coordinates as Strings
Novice thinking: "I'll just store lat/lon as text, it's simple"
Problem: Can't use spatial indexes, queries are slow, no validation.
Wrong approach:
// ❌ String storage, no spatial features
interface Location {
id: string;
name: string;
latitude: string; // "37.7749"
longitude: string; // "-122.4194"
}
// Linear scan for "nearby" queries
async function findNearby(lat: string, lon: string): Promise<Location[]> {
const all = await db.locations.findAll();
return all.filter(loc => {
const distance = calculateDistance(
parseFloat(lat),
parseFloat(lon),
parseFloat(loc.latitude),
parseFloat(loc.longitude)
);
return distance < 5000; // 5km
});
}
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 408 lines · 89 tokens per session scan A 5f9bd9c6cba9
geospatial-data-pipeline is a skill published in the GitHub repository curiositech/some_claude_skills (218 stars, last pushed 4d ago), licensed MIT. It adds 89 tokens to every session and 3,259 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
fetch-meta-from-kb
Fetch recent journals rows directly from PostgreSQL and return a JSON array containing doi, title, abstract, and date (filtered by rolling DAYS on createdat). Use when users need raw paper payloads for downstream processing without LLM filtering or hotspot report generation.
geo-infer-space
H3 hexagonal spatial indexing and multi-backend spatial operations. Use when working with H3 cells, spatial indexing, coordinate systems, raster/vector operations, or any spatial backend dispatch (H3, SRAI).
alloydb-basics
Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB Model Context Protocol (MCP) tools for automated database operations. Use when creating, configuring, or administering AlloyDB databases. Do NOT use for general PostgreSQL instances (e.g. Cloud SQL) or other GCP databases.
postgresql-table-design
Use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features.
db-repair
Auto-fix gbrain's Postgres access so the brain stays available. When any gbrain command or MCP tool result carries a GBRAINDBACCESS marker (or an operator reports the brain database is down), run the hardcoded gbrain db-repair ladder: diagnose, apply the safe tier, verify. The action is ALWAYS the hardcoded command …
dsql
Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, diagnose cluster performance, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, foreign key…