{
  "schema": "envloop.ecosystem/v1",
  "portal": "https://envloop.net",
  "platform": "https://envloop.ai",
  "console": "https://console.envloop.ai",
  "docs": "https://docs.envloop.ai",
  "api": "https://api.envloop.ai",
  "bench": "https://bench.envloop.ai",
  "packages": {
    "cli": {
      "pypi": "https://pypi.org/project/envloop-cli/",
      "install": "python -m pip install --upgrade envloop-cli",
      "entrypoints": [
        "el",
        "envloop"
      ],
      "sdk": "envloop.Client"
    },
    "envhub": {
      "pypi": "https://pypi.org/project/envloop-envhub/",
      "import_name": "envhub",
      "github": "https://github.com/EnvLoop/EnvHub",
      "role": "Asset Namespace Service (ANS) protocol, dataset/runner/recipe contracts, and verified download client"
    },
    "skill": {
      "install": "npx skills@latest add https://docs.envloop.ai --skill envloop"
    }
  },
  "rsi_equation": {
    "state": "S_t = (E_t, V_t, B_t, D_t, M_t, H_t, U_t)",
    "rollout": "R_t = Run(M_t, H_t; E_t, V_t)",
    "update": "C_{t+1} = U_t(S_t, R_t)",
    "gate": "S_{t+1} = Gate(C_{t+1}, S_t; G_t)"
  },
  "benchmarks": [
    {
      "slug": "pev-bench",
      "name": "Pev-Bench",
      "domain": "Personal-agent calibrated decisions",
      "tasks": 3885,
      "families": 7,
      "top_model": {
        "name": "Pev-27B (LoRA on Qwen3.8-27B)",
        "macro_accuracy": 0.915,
        "brier": 0.125,
        "ece": 0.065
      },
      "dataset": "https://huggingface.co/datasets/EnvLoop/Pev-Bench",
      "code": "https://github.com/EnvLoop/Pev"
    },
    {
      "slug": "cu-bench",
      "name": "cu-bench",
      "domain": "Professional Linux desktop computer use (20 apps)",
      "paired_runs": 158,
      "variants": 290,
      "top_model": {
        "name": "Claude Opus 5.5",
        "strict_pass": 83.5,
        "gui_track": 79.2,
        "code_track": 87.2
      },
      "runner": "envloop/cu-bench"
    },
    {
      "slug": "recursive-play",
      "name": "Recursive-Play",
      "domain": "Interactive environments with constructive witnesses",
      "environments": 150,
      "levels": 900,
      "top_model": {
        "name": "GPT-6 Astra",
        "complete_tasks_pct": 90,
        "cleared_levels_pct": 94.2
      },
      "dataset": "https://huggingface.co/datasets/EnvLoop/Recursive-Play-Bench"
    }
  ]
}