{
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    {
      "check": "operation",
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      "details": {
        "argv": [
          "python3",
          "-I",
          "/workspace/skills/check-reporting/scripts/prisma_cascade_check.py",
          "--round1",
          "/tmp/medsci_example/2_Screening/round1.tsv",
          "--round2",
          "/tmp/medsci_example/2_Screening/round2.tsv",
          "--round3",
          "/tmp/medsci_example/2_Screening/round3_adjudication.tsv",
          "--out",
          "/tmp/medsci_probe_out/prisma_cascade.json"
        ],
        "kind": "cli",
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        "stdout": "PASS: cascade computed. Stages: round1_total=10 \u2192 round1_include=6 \u2192 round2_include=4 \u2192 round3_include=3 \u2192 round3_exclude=1",
        "stderr": ""
      }
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    "Read README.md Installation: 'In a terminal' section (Node 18+ and Python 3.9+)",
    "Installed prerequisites with apt: nodejs 18.19.1, npm 9.2.0, git (Ubuntu 24.04); Python 3.12.3 already present",
    "Installation section 'npx medsci-skills install' via local pinned package: node bin/medsci-skills.js install (rc=0)",
    "Ran the cascade operation: python3 -I skills/check-reporting/scripts/prisma_cascade_check.py with example TSVs (rc=0, submission_safe true)"
  ],
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  "operation_scope": "Covers the Linux terminal install (62/62 skill folders verified in ~/.claude/skills and ~/.agents/skills) and one deterministic stdlib-only script. Not exercised: the agent-side skill workflows (/check-reporting, /orchestrate etc.), which need a running Claude Code/Codex client; the manuscript drift check (no --manuscript supplied); the optional Word/PDF/figure tooling reported as missing by the installer (doctor.py); and the pymupdf4llm/pandas-based scripts. No MCP server is shipped, so no tools/list applies.",
  "reasoning": "low",
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  "tool_transport": "mcp-assigned-vm",
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    "reasoning": "low"
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  "date": "2026-10-17T01:03:51.042023+00:00",
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  },
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  "pass": true,
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  "last_release_at": null,
  "furthest_model": null,
  "model": "claude-haiku-5-5",
  "what_it_did": "Installed MedSci Skills with the README's documented installer (node bin/medsci-skills.js install, the same entry point as npx medsci-skills install), then ran the bundled offline PRISMA cascade check (skills/check-reporting/scripts/prisma_cascade_check.py) on example round1/round2/round3 screening TSVs. It computed the flow counts (10 -> 6 -> 4 -> 3/1) and wrote qc JSON with submission_safe true.",
  "sandbox_source": null,
  "other_run_id": null,
  "hosting": null,
  "tested_commit": null,
  "guest_setup": null,
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  "agent_interfaces": [],
  "setup_identity": null,
  "works": null,
  "install_s": 389.465,
  "fix_id": "fix-f5b823099da63d0e46c4",
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  "test_version": "readme-ffc8770b4256cb8b179f7c65f1bbba89cc85d6191e2ebdfe5d161999e983eb8b",
  "recovery": {
    "source": "legacy-oct16-18",
    "original_run_id": "Aperivue--medsci-skills-claude-haiku-5-5-1792198335156641103",
    "historical": true,
    "ledger_sha256": "c5e6a833c182c1e2aecf69d0bd0020aec63c65d98f3e933e4b32232340312736"
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}