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 znlgis/opengis-skills --skill gdalgit clone --depth 1 https://github.com/znlgis/opengis-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/znlgis/opengis-skills/gdal)<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.
<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>- NVIDIA SkillSpector warn
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
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 | $0.00077 | $0.03842 |
| Opus 5 | $0.00039 | $0.01921 |
| Sonnet 5 | $0.00015 | $0.00768 |
| Haiku 4.5 | $0.00008 | $0.00384 |
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.
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/sort、gdal 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"
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.
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 Changed b225443cf0c4
- 12d ago First seen · 501 lines · 77 tokens per session scan A 7afbbf7163b9
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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