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RS-AgentBench
Reproduction artefact for the SIGSPATIAL '26 paper "Knowledge Channels for LLM Agents on Remote-Sensing Tasks"
1stars
0forks
Python
benchmarkllm-agentsremote-sensingsigspatial
Quality signals
ActiveNo testsNo CIThin docsNo licenseNew
InstallSKILLInstall as a Claude Code skill
Universal installANY TOOL
$ npx skillcity@latest polaries-morningstar/RS-AgentBenchAuto-detects the skill or MCP server in this repo and installs it for Claude Code, Codex, Cursor, Cline, OpenCode, Gemini CLI, Anti-Gravity, OpenClaw and Hermes.
Requires Node.js 18+ (ships with npx).
Or install manually
# Install into ~/.claude/skills/ mkdir -p ~/.claude/skills/rs-agentbench curl -fsSL https://raw.githubusercontent.com/polaries-morningstar/RS-AgentBench/main/SKILL.md -o ~/.claude/skills/rs-agentbench/SKILL.md
Loading README…
Ask a simulated agent to run this skill. It loads the real SKILL.md and reasons over your task with NVIDIA.
rs-agentbench — sandboxAI sandbox
Pick a quick prompt below or type your own — watch the agent execute this skill step by step.
guest@skillcity:~$Try a prompt