gdal

gdal is a skill for Claude Code, Codex from znlgis/opengis-skills. It costs 77 tokens per session (3,842 once invoked), scanned A, original, MIT.

A command-line toolkit for processing geographic raster data, such as satellite images and elevation maps, and vector data, such as points, lines, and areas.

In plain words
What is it for?
Use it for format conversion, coordinate reprojection, digital-elevation-model analysis, vegetation-index calculations, mosaics, and vector operations.
Why use it?
It replaces one-off scripts with standard commands for inspecting, converting, reprojecting, and analyzing geospatial files.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for format conversion, coordinate reprojection, digital-elevation-model analysis, vegetation-index calculations, mosaics, and vector operations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/znlgis/opengis-skills/gdal
Install

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.

Any agent
npx skills add znlgis/opengis-skills --skill gdal
Clone the repo
git clone --depth 1 https://github.com/znlgis/opengis-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for gdal

README.md
[![agentmods](https://agentmods.dev/badge/skills/znlgis/opengis-skills/gdal/github.svg)](https://agentmods.dev/skills/znlgis/opengis-skills/gdal)
Your own site
<a href="https://agentmods.dev/skills/znlgis/opengis-skills/gdal"><img src="https://agentmods.dev/badge/skills/znlgis/opengis-skills/gdal/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.

agentmods 80×15 button for gdal

Your own site · 80×15
<a href="https://agentmods.dev/skills/znlgis/opengis-skills/gdal"><img src="https://agentmods.dev/badge/skills/znlgis/opengis-skills/gdal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,842 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to high

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 →

  • high Privilege Escalation · line 311
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • medium MCP Rug Pull · line 75
    Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.
    Fix: Pin the image: image:tag or image@sha256:abc123
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00077 $0.03842
Opus 5 $0.00039 $0.01921
Sonnet 5 $0.00015 $0.00768
Haiku 4.5 $0.00008 $0.00384

Measured 8d ago against content hash b225443cf0c4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

gdal 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.

gis/gdal/SKILL.md · 501 lines

How it starts

The opening of the file, as written. The whole thing — 501 lines — stays where its author put it; the contents beside it link to each section on GitHub.

项目地址: https://github.com/OSGeo/gdal

官方文档: https://gdal.org/en/latest/

源码命令文档: https://gdal.org/en/latest/programs/

许可证: MIT

概述

GDAL 是地理空间数据处理的事实标准库。它提供了 50+ 个命令行工具,分为两大类:

  • OGR 工具(开放地理数据模型):处理矢量数据(点、线、面)
  • GDAL 工具:处理栅格数据(卫星影像、DEM、栅格地图)

环境准备

前置条件

GDAL 3.0+ 已预装在大多数 Linux 发行版的地理信息处理环境中。确保工具在 PATH 中:

gdalinfo --version   # 验证 GDAL 版本
ogrinfo --version    # 验证 OGR 版本

安装方法

Linux (Debian/Ubuntu)
apt-get update
apt-get install gdal-bin python3-gdal
Linux (CentOS/RHEL)
yum install gdal gdal-devel
macOS (Homebrew)
brew install gdal
Conda
conda install -c conda-forge gdal
Docker
docker run -it osgeo/gdal:latest bash

Python 绑定(可选)

某些 GDAL 工具(如 gdal_calc, gdal_merge, gdal_grid, gdal_polygonize)是 Python 脚本,需要安装 Python 绑定:

pip install GDAL
# 或
conda install -c conda-forge gdal

核心命令结构

新式 CLI (GDAL 3.9+)

GDAL 3.9 引入了统一的 CLI 接口(查看最新稳定版),并在后续版本持续完善,新增 gdal vector concave-hull/convex-hull/dissolve/sortgdal dataset check 等子命令:

gdal <command> <subcommand> [options] <inputs>

主要命令:

  • gdal info — 获取数据信息(自动检测栅格或矢量)
  • gdal vector — 矢量操作入口
  • gdal raster — 栅格操作入口
  • gdal dataset — 数据集管理

传统 CLI(广泛使用)

ogrinfo <datasource> [layer]
ogr2ogr <output> <input> [options]
gdalinfo <raster_file>
gdal_translate <input> <output> [options]
gdalwarp <input> <output> [options]

矢量数据工具(OGR)

完整参数表和高级示例见 reference/vector-tools.md

ogrinfo — 矢量数据信息查询

# 列出所有图层
ogrinfo mydata.shp

# 获取特定图层摘要
ogrinfo mydata.shp layername -so

# JSON 格式输出(GDAL 3.7+)
ogrinfo -json mydata.shp

# 显示所有要素及其属性
ogrinfo -al -geom=YES mydata.shp

# 按属性过滤
ogrinfo mydata.shp -where "AREA > 1000"

ogr2ogr — 矢量数据格式转换和处理

# 格式转换(Shapefile → GeoJSON)
ogr2ogr output.geojson input.shp

# 指定输出格式(Shapefile → GeoPackage)
ogr2ogr -f GPKG output.gpkg input.shp

# 重投影(WGS84 → Web Mercator)
ogr2ogr -t_srs EPSG:3857 output.shp input.shp

# 属性过滤
ogr2ogr output.shp input.shp -where "area > 1000"

# 选择特定字段
ogr2ogr output.shp input.shp -select "id,name,geometry"

Read the full file on GitHub · 501 lines

Files

What ships with it

2 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.

Changes

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.

  1. 8d ago Changed b225443cf0c4
  2. 12d ago First seen · 501 lines · 77 tokens per session scan A 7afbbf7163b9

Subscribe to this mod's changes

gdal is a skill published in the GitHub repository znlgis/opengis-skills (60 stars, last pushed 2d ago), licensed MIT. It adds 77 tokens to every session and 3,842 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 2026-08-30.

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