detect-objects

detect-objects is a skill for Claude Code from opengeos/geoai-skills. It costs 45 tokens per session (1,200 once invoked), scanned A, original, MIT.

A skill for running pre-trained artificial-intelligence models on geographic images. It can identify buildings, cars, ships, solar panels, parking lots, and agricultural fields, or divide an image into areas based on a text description.

In plain words
What is it for?
Use it with a raster image when you need object locations or boundaries for mapping and analysis. Choose a supported model, provide the image path, and optionally use a text prompt for text-guided segmentation; a graphics processor can improve performance.
Why use it?
Manually locating objects in large satellite or aerial images is slow. The skill turns those images into geographic output files containing the detected or outlined features.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument.

Part of the geoai-skills plugin — 8 skills shipped together

Good fit Use it with a raster image when you need object locations or boundaries for mapping and analysis. Choose a supported model, provide the image path, and optionally use a text prompt for text-guided segmentation; a graphics processor can improve performance.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/opengeos/geoai-skills/detect-objects
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 opengeos/geoai-skills --skill detect-objects
Clone the repo
git clone --depth 1 https://github.com/opengeos/geoai-skills

Made for: Claude Code.

Or install geoai-skills, the plugin that ships this one along with the rest of its 8 skills.

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 detect-objects

README.md
[![agentmods](https://agentmods.dev/badge/skills/opengeos/geoai-skills/detect-objects.svg)](https://agentmods.dev/skills/opengeos/geoai-skills/detect-objects)
Your own site
<a href="https://agentmods.dev/skills/opengeos/geoai-skills/detect-objects"><img src="https://agentmods.dev/badge/skills/opengeos/geoai-skills/detect-objects.svg" alt="Measured on agentmods" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,200 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.
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 $0.00045 $0.01200
Opus 5 $0.00023 $0.00600
Sonnet 5 $0.00009 $0.00240
Haiku 4.5 $0.00005 $0.00120

Measured 8d ago against content hash 3a63b1522dce, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

detect-objects 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.

skills/detect-objects/SKILL.md · 143 lines

How it starts

The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are helping the user run AI object detection on geospatial imagery using geoai.

Input: $@

Follow these steps in order.

Step 1 -- Parse arguments

Extract:

  • $0 as the model name: buildings, cars, ships, solar-panels, parking-lots, agriculture, or grounded-sam
  • $1 as the input raster path
  • --text PROMPT for GroundedSAM text-prompted segmentation (required when model is grounded-sam)
  • --output FILE for the output vector file (default: ./<model>_detections.gpkg)

If the model name is not recognized, list the available models and ask the user to pick one.

Model mapping:

Argument GeoAI Class
buildings geoai.BuildingFootprintExtractor
cars geoai.CarDetector
ships geoai.ShipDetector
solar-panels geoai.SolarPanelDetector
parking-lots geoai.ParkingSplotDetector
agriculture geoai.AgricultureFieldDelineator
grounded-sam geoai.GroundedSAM

Step 2 -- Check GPU availability

python3 -c "
import torch
if torch.cuda.is_available():
    print(f'GPU: {torch.cuda.get_device_name(0)}')
    print(f'CUDA: {torch.version.cuda}')
    print(f'Memory: {torch.cuda.get_device_properties(0).total_mem / 1e9:.1f} GB')
else:
    print('GPU: not available (CPU mode)')
    print('Warning: inference will be significantly slower without a GPU')
"

If no GPU is available, warn the user but continue.

Step 3 -- Resolve the input file

If $1 looks like an absolute path, use it directly. Otherwise:

find "$PWD" -name "$1" -not -path '*/.git/*' 2>/dev/null

If no file specified and state exists, check for recently inspected/downloaded files:

STATE_DIR=""
test -f .geoai-skills/state.json && STATE_DIR=".geoai-skills"
PROJECT_ROOT="$(git rev-parse --show-toplevel 2>/dev/null || echo "$PWD")"
PROJECT_ID="$(echo "$PROJECT_ROOT" | tr '/' '-')"
test -f "$HOME/.geoai-skills/$PROJECT_ID/state.json" && STATE_DIR="$HOME/.geoai-skills/$PROJECT_ID"

Read the full file on GitHub · 143 lines

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 First seen · 143 lines · 45 tokens per session scan A 3a63b1522dce

Subscribe to this mod's changes

detect-objects is a skill published in the GitHub repository opengeos/geoai-skills (30 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 1,200 once invoked, about $0.0002 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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