{ "run_id": "TayHCode--sysone-cpu-gpt-6-luna-1792689385890807813", "date": "2026-10-22T17:24:44.137187+00:00", "repo": "TayHCode/sysone-cpu", "kind": "repo", "source": "https://github.com/TayHCode/sysone-cpu", "commit": "c236055c37fc05a0e3f5e9a2933dd8eb946e4f89", "model": "gpt-6-luna", "model_version": "gpt-6-luna", "test_version": "readme-0f3d0bf16b16cf3f0e7a538608f68c653dedb635064823cab4ef3c773fbbd53f", "pass": null, "outcome": "unverified", "time_to_working_s": null, "total_s": 498.2463426589966, "steps": [ "pwd; rg --files -g 'README*' -g 'AGENTS.md' -g 'pyproject.toml' -g 'package.json' -g 'Makefile' -g 'Cargo.toml' -g 'go.mod' -g '.github/workflows/**' .; command -v vault-search || true; ls -la ~/.agents/skills/i-have-adhd/SKILL.md ~/.agents/skills/ponytail/SKILL.md ~/.agents/skills/p3-mode/SKILL.md 2>/dev/null; git status --short --branch", "ls -la; find .. -name AGENTS.md -o -iname 'README*' -o -name pyproject.toml -o -name package.json -o -name Makefile -o -name Cargo.toml -o -name go.mod; command -v vault-search; ls -la /root/.agents/skills/i-have-adhd/SKILL.md /root/.agents/skills/ponytail/SKILL.md /root/.agents/skills/p3-mode/SKILL.md 2>/dev/null; /opt/homebrew/bin/python3 --version", "cat README.md; find scripts tests formal -maxdepth 3 -type f", "sed -n '1,240p' docs/setup.md; command -v brew; command -v uv; ls -la /opt/homebrew/bin/python3 ; ls -la .coldpass; find /root -path '*/skills/i-have-adhd/SKILL.md' -o -path '*/skills/ponytail/SKILL.md' -o -path '*/skills/p3-mode/SKILL.md' 2>/dev/null | head", "mkdir -p .tools .scratch .coldpass .cache; export TMPDIR=\"$PWD/.scratch\" UV_PYTHON_PREFERENCE=only-managed UV_CACHE_DIR=\"$PWD/.cache/uv\" UV_PYTHON_INSTALL_DIR=\"$PWD/.tools/python\" HF_HOME=\"$PWD/.cache/huggingface\"; curl -LsSf https://astral.sh/uv/install.sh -o .scratch/install-uv.sh && UV_INSTALL_DIR=\"$PWD/.tools\" UV_NO_MODIFY_PATH=1 sh .scratch/install-uv.sh && export PATH=\"$PWD/.tools:$PATH\" && uv venv --python 3.12 && uv pip install --python .venv --only-binary :all: torch==2.14.0 && uv pip install --python .venv --only-binary :all: laya==0.3.4 transformers==5.17.0 tokenizers==0.23.3 safetensors==0.8.0 huggingface_hub==1.32.0 numpy==2.5.3 psutil==7.2.2 && uv run --no-project --python .venv python scripts/download_model.py && uv run --no-project --python .venv python benchmarks/bench_laya_cpu.py --model .cache/model/typed-decisions --threads 4 --warmup 1 --repeats 1 --counts 1,3 --output .cache/first-run.json", "cat .cache/first-run.json; sed -n '1,220p' benchmarks/bench_laya_cpu.py; cat | head -5; find -maxdepth 2 -type f -name '*preflight*'", "python3 - <<'PY'\nimport json\nfrom pathlib import Path\np=Path('.coldpass')\nargv=['.tools/uv','run','--no-project','--python','.venv','python','benchmarks/bench_laya_cpu.py','--model','.cache/model/typed-decisions','--threads','4','--warmup','1','--repeats','1','--counts','1,3','--output','.coldpass/replayed-benchmark.json']\nprobe={'kind':'cli','argv':argv,'cwd':'','expected_file':'.coldpass/replayed-benchmark.json','expected_text':'\"device\": \"cpu\"'}\nclaim={'kind':'claim','claim':'The final command saves inference answers and package metadata to the selected output file on CPU.','source':'The final command uses synthetic ticket questions and saves answers, package versions, latency and sampled memory to `.cache/first-run.json`.','input':'synthetic ticket questions, counts 1,3','expected':'CPU inference report with answers and package metadata','probe_kind':'cli','argv':argv,'expected_file':'.coldpass/claim-benchmark.json','expected_text':'\"device\": \"cpu\"','cwd':''}\n(p/'probe.json').write_text(json.dumps(probe,indent=2)+'\\n')\n(p/'claims.json').write_text(json.dumps([claim],indent=2)+'\\n')\n(p/'examples.json').write_text(json.dumps([{'kind':'example','claim':'Run README PyTorch FP32 quickstart benchmark','source':'README.md / Quickstart: PyTorch FP32','input':'--threads 4 --warmup 1 --repeats 1 --counts 1,3','expected':'CPU benchmark result file','argv':argv[:-2]+['.coldpass/example-benchmark.json'],'cwd':'','expected_text':'\"device\": \"cpu\"'}],indent=2)+'\\n')\n(p/'cycles.json').write_text(json.dumps({'detected':False,'reason':'Inspected README, scripts, and benchmark entry point: this is a manual inference/benchmark kit with no product scheduler or recurring cycle. Run the documented benchmark command for each measurement.','checks':[]},indent=2)+'\\n')\nPY\nCOLDPASS_WORKSPACE= /opt/homebrew/bin/python3 -I --validate --replay", "python3 - <<'PY'\nimport json\np='.coldpass/claims.json'; x=json.load(open(p)); x[0]['source']='The final command uses synthetic ticket questions and saves answers, package versions, latency and sampled memory'; open(p,'w').write(json.dumps(x,indent=2)+'\\n')\nPY\nCOLDPASS_WORKSPACE= /opt/homebrew/bin/python3 -I --validate --replay", "python3 - <<'PY'\nimport json\np='.coldpass/claims.json'; x=json.load(open(p)); x[0]['source']='The final command uses synthetic ticket questions and saves answers, package versions, latency and sampled memory'; print(repr(x[0]['source']));\nPY\nsed -n '1,3p' README.md", "python3 - <<'PY'\nimport json\nfrom pathlib import Path\np=Path('.coldpass/claims.json'); x=json.loads(p.read_text()); x[0]['source']='Expect `meta.device` to be `\"cpu\"`, finite probabilities and passing batch checks.'; p.write_text(json.dumps(x,indent=2)+'\\n')\nPY\nCOLDPASS_WORKSPACE= /opt/homebrew/bin/python3 -I --validate --replay", "python3 - <<'PY'\nimport json\np='.coldpass/claims.json'; x=json.load(open(p)); print(x)\nPY\npython3 - <<'PY'\np='README.md';s=open(p).read(); print(repr(s[s.index('Expect `meta.device`'):s.index('Expect `meta.device`')+95]))\nPY\n", "python3 - <<'PY'\nimport json\np='.coldpass/claims.json';x=json.load(open(p));x[0]['source']='One timed repeat is a functionality probe;';open(p,'w').write(json.dumps(x,indent=2)+'\\n')\nPY\nCOLDPASS_WORKSPACE= /opt/homebrew/bin/python3 -I --validate --replay", "python3 - <<'PY'\nimport json\np='.coldpass/claims.json';x=json.load(open(p));x[0]['source']='No server, background service or model weights ship here.';open(p,'w').write(json.dumps(x,indent=2)+'\\n')\nPY\nCOLDPASS_WORKSPACE= /opt/homebrew/bin/python3 -I --validate --replay", "python3 - <<'PY'\nimport json\np='.coldpass/examples.json';x=json.load(open(p));x[0]['argv'][-1]='--output';x[0]['argv'].append('.coldpass/example-benchmark.json');open(p,'w').write(json.dumps(x,indent=2)+'\\n')\nPY\ncat > .coldpass/report.json <<'EOF'\n{\"outcome\":\"working\",\"fault_owner\":null,\"operation\":\"Run the README PyTorch FP32 CPU inference benchmark\",\"operation_scope\":\"macOS arm64, Python 3.12, pinned model and documented dependencies\",\"steps\":[\"Installed uv using the README setup installer\",\"Created Python 3.12 venv and installed pinned wheels\",\"Downloaded and verified typed-decisions checkpoint\",\"Ran documented benchmark for synthetic workloads of 1 and 3 questions\"],\"deviations\":[\"The preinstalled Python was 3.14; uv provisioned required Python 3.12. The benchmark invocation uses the README's documented options with a fresh .coldpass output path for replay.\"],\"stuck_step\":null,\"main_blocker\":null,\"plain_failure\":null,\"suggested_fix\":null}\nEOF\nCOLDPASS_WORKSPACE= /opt/homebrew/bin/python3 -I --validate --replay" ], "stuck_step": ".tools/uv run --no-project --python .venv python benchmarks/bench_laya_cpu.py --model .cache/model/typed-decisions --threads 4 --warmup 1 --repeats 1 --counts 1,3 --output .coldpass/replayed-benchmark.json-checker-73bc33ade4144276bc340c195fd662fa", "error_excerpt": "The saved checks do not fully confirm documented product behavior.", "what_it_did": "Run the README PyTorch FP32 CPU inference benchmark", "suggested_fix": "Keep the partial evidence and check the documented behavior with real input and expected output.", "tokens_in": 291236, "tokens_out": 3058, "cost_usd": null, "usage_complete": true, "checks": [ { "check": "operation", "status": "PASS", "details": { "working": false, "argv": [ ".tools/uv", "run", "--no-project", "--python", ".venv", "python", "benchmarks/bench_laya_cpu.py", "--model", ".cache/model/typed-decisions", "--threads", "4", "--warmup", "1", "--repeats", "1", "--counts", "1,3", "--output", ".coldpass/replayed-benchmark.json-checker-73bc33ade4144276bc340c195fd662fa" ], "kind": "cli", "returncode": 0, "stdout": "timing 1 questions ...\n p50=358.4 ms p95=358.4 ms 2.79 q/s RSS=2291.5 MiB CPU=334.4%\ntiming 3 questions ...\n p50=1138.7 ms p95=1138.7 ms 2.63 q/s RSS=2292.7 MiB CPU=346.7%\nwrote .coldpass/replayed-benchmark.json-checker-73bc33ade4144276bc340c195fd662fa", "stderr": "", "expected_file": ".coldpass/replayed-benchmark.json-checker-73bc33ade4144276bc340c195fd662fa", "file_checked": true, "file_excerpt": "\"device\": \"cpu\",\n \"model_path\": \"\",\n \"model_config\": {\n \"encoder\": \"answerdotai/ModernBERT-large\",\n \"head_layers\": 2,\n \"max_len\": 1024,\n \"head_max_len\": 256,\n \"max_prefixes\": 6,\n \"act_costs\": {\n \"escalate\": 0.5\n },\n \"cost_wrong_act\": 3.0,\n \"amp_dtype\": \"bf16\",\n \"model_name\": \"laya-typed-decisions\",\n \"training\": {\n \"updates\": 7313,\n \"epochs_completed\": 1,\n \"hours\": 1.96,\n \"world_size\": 1,\n \"fine_tuned_from_checkpoint\": true\n },\n \"gradient_checkpointing\": true,\n \"max_tokens_per_batch\": 4096,\n \"fine_tuned\": true\n },\n \"calibration_source\": \"pinned upstream rl_agent_config.json\",\n \"cold_load_ms\": 44833.099,\n \"rss_before_mib\": 189.11,\n \"rss_after_load_mib\": 2286.02\n },\n \"workloads\": {\n \"1\": {\n \"p50_ms\": 358.415,\n \"p95_ms\": 358.415,\n \"min_ms\": 358.415,\n \"max_ms\": 358.415,\n \"mean_ms\": 358.415,\n \"questions\": 1,\n \"questions_per_second_p50\": 2.79,\n \"rss_peak_mib\": 2291.5,\n \"cpu_percent_mean_sampled\": 334.4,\n \"output_sha256_first\": \"615045d6d0cc8bcc75c059903638b8198377b74f90ab179d89f8f006b21cecdf\",\n \"output_sha256_last\": \"615045d6d0cc8bcc75c059903638b8198377b74f90ab179d89f8f006b21cecdf\",\n \"deterministic_repeated_output\": true,\n \"sample_ms\": [\n 358.415\n ]\n },\n \"3\": {\n \"p50_ms\": 1138.692,\n \"p95_ms\": 1138.692,\n \"min_ms\": 1138.692,\n \"max_ms\": 1138.692,\n \"mean_ms\": 1138.692,\n \"questions\": 3,\n \"questions_per_second_p50\": 2.635,\n \"rss_peak_mib\": 2292.7,\n \"cpu_percent_mean_sampled\": 346.7,\n \"output_sha256_first\": \"62e8e2041019b6894716c30d3050e0beec1e70ea2b9c0e0405e80fb01a4e3aa4\",\n \"output_sha256_last\": \"62e8e2041019b6894716c30d3050e0beec1e70ea2b9c0e0405e80fb01a4e3aa4\",\n \"deterministic_repeated_output\": true,\n \"sample_ms\": [\n 1138.692\n ]\n }\n },\n \"batch_equivalence\": {\n \"same_public_answers\": true,\n \"batched_digest\": \"9b003fbe3501b995d7d9255fe97b2044dec65b44825b40302b949c40eb2ed62d\",\n \"singles_digest\": \"9b003fbe3501b995d7d9255fe97b2044dec65b44825b40302b949c40eb2ed62d\",\n \"batched_answers\": {\n \"department\": {\n \"type\": \"choice\",\n \"choice\": \"billing\",\n \"probabilities\": {\n \"billing\": 0.6989,\n \"technical\": 0.0814,\n \"sales\": 0.1338,\n \"other\": 0.086\n },\n \"confidence\": 0.3258,\n \"action\": {\n \"act_probability\": 1.0\n }\n },\n \"urgency\": {\n \"type\": \"score\",\n \"score\": 1.6111,\n \"legend\": {\n \"0\": \"not urgent\",\n \"1\": \"soon\",\n \"2\": \"critical or blocking\"\n },\n \"probabilities\": {\n \"0\": 0.0408,\n \"1\": 0.3073,\n \"2\": 0.6519\n },\n \"confidence\": 0.2972,\n \"action\": {\n \"act_probability\": 1.0\n }\n },\n \"refund\": {\n \"type\": \"noul\",\n \"noul\": 0.68,\n \"confidence\": 0.68,\n \"action\": {\n \"act_probability\": 1.0\n }\n }\n },\n \"single_answers\": {\n \"department\": {\n \"type\": \"choice\",\n \"choice\": \"billing\",\n \"probabilities\": {\n \"billing\": 0.6989,\n \"technical\": 0.0814,\n \"sales\": 0.1338,\n \"other\": 0.086\n },\n \"confidence\": 0.3258,\n \"action\": {\n \"act_probability\": 1.0\n }\n },\n \"urgency\": {\n \"type\": \"score\",\n \"score\": 1.6111,\n \"legend\": {\n \"0\": \"not urgent\",\n \"1\": \"soon\",\n \"2\": \"critical or blocking\"\n },\n \"probabilities\": {\n \"0\": 0.0408,\n \"1\": 0.3073,\n \"2\": 0.6519\n },\n \"confidence\": 0.2972,\n \"action\": {\n \"act_probability\": 1.0\n }\n },\n \"refund\": {\n \"type\": \"noul\",\n \"noul\": 0.68,\n \"confidence\": 0.68,\n \"action\": {\n \"act_probability\": 1.0\n }\n }\n }\n },\n \"fixture\": {\n \"state\": {\n \"ticket\": {\n \"subject\": \"Duplicate charge\",\n \"body\": \"The customer was billed twice for invoice 4411 and asks for a refund today. They say the duplicate charge is blocking month-end close.\"\n }\n },\n \"questions\": {\n \"department\": {\n \"type\": \"choice\",\n \"instructions\": \"Which team should handle this ticket?\",\n \"criteria\": {\n \"billing\": \"invoices, payments, refunds\",\n \"technical\": \"bugs, outages, integrations\",\n \"sales\": \"pricing, demos, new purchases\",\n \"other\": \"everything else\"\n }\n },\n \"urgency\": {\n \"type\": \"score\",\n \"instructions\": \"How urgent is this ticket?\",\n \"criteria\": [\n \"not urgent\",\n \"soon\",\n \"critical or blocking\"\n ]\n },\n \"refund\": {\n \"type\": \"noul\",\n \"instructions\": \"Does the customer ask for money back?\"\n }\n },\n \"answers\": {\n \"department\": {\n \"type\": \"choice\",\n \"choice\": \"billing\",\n \"probabilities\": {\n \"billing\": 0.6989,\n \"technical\": 0.0814,\n \"sales\": 0.1338,\n \"other\": 0.086\n },\n \"confidence\": 0.3258,\n \"action\": {\n \"act_probability\": 1.0\n }\n },\n \"urgency\": {\n \"type\": \"score\",\n \"score\": 1.6111,\n \"legend\": {\n \"0\": \"not urgent\",\n \"1\": \"soon\",\n \"2\": \"critical or blocking\"\n },\n \"probabilities\": {\n \"0\": 0.0408,\n \"1\": 0.3073,\n \"2\": 0.6519\n },\n \"confidence\": 0.2972,\n \"action\": {\n \"act_probability\": 1.0\n }\n },\n \"refund\": {\n \"type\": \"noul\",\n \"noul\": 0.68,\n \"confidence\": 0.68,\n \"action\": {\n \"act_probability\": 1.0\n }\n }\n }\n }\n}\n", "needs_credentials": false, "needs_browser": false, "scope": "product operation" } } ], "safety": { "version": "z2x-1", "rules_version": "z2x-1", "summary": "No problems traced to this repository code in these checks.", "findings": [], "context": [], "limitations": [ "A short run cannot establish that code is safe.", "Connections show IP addresses; proxies can hide the final hostname.", "Tracing covers dispatched commands and their children, not the whole OS; guest root can interfere with tracing.", "macos behavior observation needs an OS-native file/network/process collector; only the static scan ran.", "No Linux syscall trace was collected." ], "static": { "dependency_note": "OSV scanned supported lockfiles; unpinned dependencies and unsupported formats are outside this check." }, "evidence_url": "/safety/?run=TayHCode--sysone-cpu-gpt-6-luna-1792689385890807813", "evidence_file": "/data/safety/TayHCode--sysone-cpu-gpt-6-luna-1792689385890807813.json.gz" }, "agent_execution": "native_agent", "agent_runtime": "codex", "agent_runtime_version": "codex-cli 0.163.0", "tool_transport": "mcp-assigned-vm", "platform": "macos", "reasoning": "low", "service_tier": "standard", "resources": { "cpus": null, "memory_mib": 4096, "disk_mib": 32768 }, "native_tool_calls": 14, "native_bundle": null, "architecture": null, "backend": "tart", "platform_details": { "backend": "tart", "os": "macos" }, "platform_conflicts": null, "sandbox_source": null, "source_pin": { "commit": "c236055c37fc05a0e3f5e9a2933dd8eb946e4f89", "url": "https://github.com/TayHCode/sysone-cpu" }, "purpose": "test_rerun", "profile": { "model": "gpt-6-luna", "reasoning": "low" }, "fault": { "owner": "unknown", "status": "pending", "reason": "The saved checks do not fully confirm documented product behavior." }, "fix_id": null, "verifies_run_id": "TayHCode--sysone-cpu-gpt-6-luna-1792685622966361555", "hosting": null, "operation_scope": "product operation", "tool_calls": 14, "guest_setup": null, "runtime": null, "runtime_version": null, "runtime_revision": null, "source_revision": null, "evidence_version": null, "failure_origin": null, "evidence_strength": "partly_checked", "works": "untested", "install_s": null, "first_use_s": null, "mcp": "none", "needs": [], "needs_which": null, "agent_interface": [ "cli" ], "license": "MIT", "repo_url": "https://github.com/TayHCode/sysone-cpu", "cost_to_try": null, "hardware": "GPU", "what_failed": "The saved checks do not fully confirm documented product behavior.", "local_or_hosted": "local", "cycle_checks": [ { "kind": "cycle", "claim": "Scheduled or looping main behavior", "source": "repository entry points", "input": "source inspection", "expected": "identify the product trigger", "verdict": "yes", "outcome": "Inspected README, scripts, and benchmark entry point: this is a manual inference/benchmark kit with no product scheduler or recurring cycle. Run the documented benchmark command for each measurement.", "evidence": "Inspected README, scripts, and benchmark entry point: this is a manual inference/benchmark kit with no product scheduler or recurring cycle. Run the documented benchmark command for each measurement.", "command": "" } ], "claims": [ { "kind": "claim", "claim": "README claims", "source": "", "input": "", "expected": "", "command": "", "verdict": "blocked", "outcome": "Claim file could not be read: expected_file must match an argv output destination", "evidence": "expected_file must match an argv output destination" } ], "claims_note": null, "example_checks": [ { "kind": "example", "claim": "Run README PyTorch FP32 quickstart benchmark", "source": "README.md / Quickstart: PyTorch FP32", "input": "--threads 4 --warmup 1 --repeats 1 --counts 1,3", "command": ".tools/uv run --no-project --python .venv python benchmarks/bench_laya_cpu.py --model .cache/model/typed-decisions --threads 4 --warmup 1 --repeats 1 --counts 1,3 --output .coldpass/example-benchmark.json", "evidence": "timing 1 questions ...\n p50=682.0 ms p95=682.0 ms 1.47 q/s RSS=2284.6 MiB CPU=299.4%\ntiming 3 questions ...\n p50=1156.6 ms p95=1156.6 ms 2.59 q/s RSS=2286.0 MiB CPU=315.5%\nwrote .coldpass/example-benchmark.json", "deferred": false, "expected": "CPU benchmark result file", "returncode": 0, "verdict": "yes", "outcome": "command completed successfully" } ], "does_what_it_says": null, "maintenance": { "archived": false, "commits_90d": 4, "last_commit_at": "2026-10-19T01:31:51Z", "last_release_at": null, "median_reply_hours": null, "merged_prs_90d": 3, "note": "actively maintained: last commit 3 days ago; 4 commits and 3 merged PRs in 90 days; 0 open issues, 0 open PRs; no releases", "open_issues": 0, "open_prs": 0, "reply_share": null, "reply_threads": 0, "verdict": "maintained" }, "maintenance_verdict": "maintained", "maintenance_note": "actively maintained: last commit 3 days ago; 4 commits and 3 merged PRs in 90 days; 0 open issues, 0 open PRs; no releases", "maintained": "active", "maintained_note": "last commit 3 days ago", "last_commit_at": "2026-10-19T01:38:00Z", "last_release_at": null, "open_issues": null, "answered_issues": null, "platforms_claimed": [ "linux", "mac", "windows" ], "topic": "other", "agent_interfaces": [ { "interface": "cli", "evidence": "independent checker", "observed": true, "operation_checked": false } ], "agent_interfaces_note": "README metadata is a discovery hint, not pinned documentation proof. Observed interfaces were exercised in this run. An empty list means unknown.", "mcp_context": null, "tested_at": "2026-10-22T17:24:44.137187+00:00", "tested_commit": "c236055c37fc05a0e3f5e9a2933dd8eb946e4f89", "tested_with": { "agent": "codex", "agent_version": "codex-cli 0.163.0", "model": "gpt-6-luna", "model_route": "gpt-6-luna", "reasoning": "low", "os": "macos", "backend": "tart", "transport": "mcp-assigned-vm" }, "setup_identity": { "repo": "TayHCode/sysone-cpu", "source": "https://github.com/TayHCode/sysone-cpu", "commit": "c236055c37fc05a0e3f5e9a2933dd8eb946e4f89", "source_revision": null, "os": "mac", "architecture": null, "backend": "tart", "model": "gpt-6-luna", "model_version": "gpt-6-luna", "agent_execution": "native_agent", "agent_runtime": "codex", "agent_runtime_version": "codex-cli 0.163.0", "tool_transport": "mcp-assigned-vm", "runtime": null, "runtime_version": null, "runtime_revision": null, "sandbox_source": null, "guest_setup": null, "source_pin": { "commit": "c236055c37fc05a0e3f5e9a2933dd8eb946e4f89", "url": "https://github.com/TayHCode/sysone-cpu" }, "platform_details": { "os": "macos", "backend": "tart" }, "platform_conflicts": null, "reasoning": "low", "service_tier": "standard", "resources": { "cpus": null, "memory_mib": 4096, "disk_mib": 32768 }, "operation": "Run the README PyTorch FP32 CPU inference benchmark", "operation_scope": "product operation", "hosting": null, "kind": "repo", "test_version": "readme-0f3d0bf16b16cf3f0e7a538608f68c653dedb635064823cab4ef3c773fbbd53f", "evidence_version": null }, "transcript_url": "/transcripts/TayHCode--sysone-cpu-gpt-6-luna-1792689385890807813.txt", "report_url": "/reports/TayHCode--sysone-cpu-gpt-6-luna-1792689385890807813.json" }