Spotter: Official codebase for Spotter: Let the Embodied Model Lead, and the VLM Reflect for It

by zqc3117 · Agent Tool · ★ 203

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 62/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

embodied-aillm-agentqwenrobocasarobodojorobot-learningrobot-manipulationroboticsrobotwinruntime-monitoring-system

Quick Facts

Stars203
Forks25
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score62/100
Last Updated2026-10-20
Created2026-09-29
Platformspython
Est. Tokens~19k

About Spotter

Spotter: Let the Embodied Model Lead, and the VLM Reflect for It If our project helps you, please give us a star ⭐ on GitHub to support us. pi0.5 · [Cosmos Policy](https://huggingface.co/nvidia/Cosmos-

Compatible Skills

These tools work well together with Spotter for enhanced workflows:

  • rosclaw — semantic(0.49)+complementary+rare_topics+same_lang+similar_pop+shared_platform (72%)
  • PhyAgentOS — semantic(0.38)+complementary+rare_topics+same_lang+similar_pop+shared_platform (68%)
  • jev-libero — semantic(0.28)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)

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    RAI is a vendor agnostic agentic framework for Physical AI robotics, utilizing ROS 2 tools to perform complex

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  • quackd by rokbenko · ⭐ 269

    One CLI for all your robots. Connect them, command them, and let them work together, each with an LLM for a br

  • rosclaw by ros-claw · ⭐ 229

    Physical AI runtime for embodied agents — governed action, verified experience, physical memory, and skill evo

  • Awesome-LLM-Papers-Comprehensive-Topics by shure-dev · ⭐ 223

    Awesome LLM Papers and repos on very comprehensive topics.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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