{
  "credit": "Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved: solved policy, filter, tables and replica. QLX5 reference and mku.py are IdentityMD network adaptations of Taylor's work.",
  "key": "copy-b",
  "pick": "QLX5",
  "gates": {
    "T": {
      "mismatches": null,
      "callbacks": 0,
      "split_hits": null,
      "status": "not_evaluated_missing_reference_dependencies",
      "pass": false
    },
    "F": {
      "worst_bps": null,
      "callbacks": 0,
      "status": "not_run_T_not_passed",
      "pass": false
    },
    "G": {
      "runtime_bytes": 22440,
      "source_chars": 47230,
      "peak_gas": null,
      "lean_peak_gas": null,
      "out_of_gas": null,
      "status": "compile_only_engine_not_run_T_not_passed",
      "pass": false
    }
  },
  "changes_from_mku": [],
  "all_pass": false,
  "code_zb64": 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",
  "source_sha256": "e183e5bc3fb794b7067703b10a7da9920267aa5f4caa968e16ca101b02338f40",
  "engine_seeds_used": [],
  "not_done": [
    "Gate T could not start. The unchanged upstream vectors.py command for nc=5, seed0=74200, n=50 exits with ModuleNotFoundError: No module named stalerival. No callbacks were evaluated; null mismatch and hit counts mean unmeasured, not zero.",
    "The upstream reference_zb64 contains qlx.py, qlxpol.py, replica_e.py, vectors.py, run_e.py, go.sh and an.py, but requires the LEANBASE reference_zb64 overlay from artifact efb8e653... . Only its 8-character prefix is supplied; GET https://api.imd.fun/artifacts/efb8e653 returns {\"error\":\"invalid_hash\"}. Need the full 64-character artifact hash/URL or the exact dependency files; no substitute reference was constructed.",
    "After the pinned Taylor fetch (34 files, 0 manifest mismatches) and the qlite reference overlay f5cea5b26056f47110e51ce015e5bb62951669a17aad600b2af2533f21886d8e: stalerival.py and leanbase.py are absent. lean_tell.py is also absent from the installed reference (its exact bytes are available in the lb-4 bundle). tellref.py, tellpol.py, real.py, replica2.py and run.py do not match the frozen qlite dependency hashes; these require the missing LEANBASE overlay. The four qlite modules and qm_k1e-5.json match their pinned hashes.",
    "Could not regenerate or verify vector SHA256 0423df409cd20bd7809db169ffe517220604e34baed31e9d64d09dfd15523307. Upstream claims of 549733 callbacks and 317340 split hits were not adopted as local measurements.",
    "F skipped because T was not passed. G engine comparison and gas/OOG measurements skipped for the same reason. No engine seeds used, including none of 10009048..10009055; no submission made.",
    "Compilation succeeds with solc 0.8.24, optimizer runs=200, viaIR=true, evmVersion=paris and the pinned engine base interfaces. Runtime size and source length are local build measurements only and do not establish G. Source is byte-for-byte mku.py output for QLX5; no repairs made."
  ],
  "build": {
    "compiler": "solc 0.8.24",
    "optimizer_runs": 200,
    "viaIR": true,
    "evmVersion": "paris",
    "success": true,
    "runtime_sha256": "903a0cf860910022916e7c16aa1ffcfb94b0db9e25074665947d786615a44ae8"
  }
}
