Borrowing it
Nothing to install: this file belongs to gpt-cmdr/ras-commander. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/gpt-cmdr/ras-commander/main/.claude/skills/hecras_export_cloud-native/SKILL.mdgit clone --depth 1 https://github.com/gpt-cmdr/ras-commanderWrote 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/gpt-cmdr/ras-commander/hecras_export_cloud-native)<a href="https://agentmods.dev/skills/gpt-cmdr/ras-commander/hecras_export_cloud-native"><img src="https://agentmods.dev/badge/skills/gpt-cmdr/ras-commander/hecras_export_cloud-native.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00154 | $0.02479 |
| Opus 5 | $0.00077 | $0.01239 |
| Sonnet 5 | $0.00031 | $0.00496 |
| Haiku 4.5 | $0.00015 | $0.00248 |
Grade A, and why
hecras_export_cloud-native 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 8d 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exporting HEC-RAS to Cloud-Native Formats
When the user asks to export HEC-RAS results to GeoParquet, PMTiles, or PostGIS, use this skill with the ras2cng CLI (RAS to Cloud Native GIS). This CLI wraps ras-commander parsers to export HEC-RAS geometry and results to GeoParquet, vector/raster PMTiles, and PostGIS.
Repo: C:\GH\ras2cng
Quick Start
1. Export Geometry to GeoParquet
# HDF geometry (*.g??.hdf) — exports mesh cell polygons by default
ras2cng geometry model.g01.hdf mesh_cells.parquet
# Text geometry (*.g01) — exports cross section cut lines by default
ras2cng geometry model.g01 cross_sections.parquet
# Select a specific layer
ras2cng geometry model.g01.hdf mesh_cells.parquet --layer mesh_cells
ras2cng geometry model.g01.hdf xs.parquet --layer cross_sections
ras2cng geometry model.g01.hdf cl.parquet --layer centerlines
2. Export Results to GeoParquet
# Single variable (default: Maximum Depth)
ras2cng results model.p01.hdf max_depth.parquet
# Specific variable
ras2cng results model.p01.hdf max_wse.parquet --var "Maximum Water Surface"
# Join results onto polygon geometry (results become spatial polygons, not points)
ras2cng results model.p01.hdf max_depth.parquet \
--geometry mesh_cells.parquet \
--var "Maximum Depth"
# Export ALL available summary variables to a directory
ras2cng results model.p01.hdf ./results_dir/ --all \
--geometry mesh_cells.parquet
3. Query with DuckDB
# SQL query — table alias is always `_`
ras2cng query max_depth.parquet "SELECT mesh_name, AVG(maximum_depth) FROM _ GROUP BY mesh_name"
# Save results
ras2cng query max_depth.parquet "SELECT * FROM _ WHERE maximum_depth > 5" --output deep.csv
ras2cng query max_depth.parquet "SELECT * FROM _ WHERE maximum_depth > 5" --output deep.parquet
4. Generate PMTiles
# Vector PMTiles from GeoParquet (requires tippecanoe and pmtiles CLI)
ras2cng pmtiles mesh_cells.parquet mesh_cells.pmtiles --layer mesh_cells
# With zoom range
ras2cng pmtiles mesh_cells.parquet mesh_cells.pmtiles \
--layer mesh_cells --min-zoom 8 --max-zoom 14
# Raster PMTiles from GeoTIFF (requires gdal_translate and pmtiles CLI)
ras2cng pmtiles results.tif results.pmtiles
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.
- 8d ago First seen · 285 lines · 154 tokens per session scan A 9fc674acec91
hecras_export_cloud-native is a skill published in the GitHub repository gpt-cmdr/ras-commander (79 stars, last pushed yesterday), licensed MIT. It adds 154 tokens to every session and 2,479 once invoked, about $0.0008 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 2026-08-30.
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