{
  "run_id": "TayHCode--tailscale-agent-access-gpt-6-luna-1792683707660888275",
  "checker": {
    "claims": [
      {
        "claim": "The summary describes the starter policy grants.",
        "command": "python3 agent_access.py summary",
        "evidence": "agent-a (tag:agent-agent-a)\n  Everything preset: grants all IP traffic to all destinations.\n\nagent-b (tag:agent-agent-b)\n  Everything preset: grants all IP traffic to all destinations.\n\nagent-c (tag:agent-agent-c)\n  Everything preset: grants all IP traffic to all destinations.\n",
        "expected": "agent-a uses the everything preset and grants all IP traffic to all destinations",
        "input": "checked-in policy.json",
        "kind": "claim",
        "outcome": "Real input produced the expected result: agent-a (tag:agent-agent-a)",
        "returncode": 0,
        "source": "Each agent has a `preset`: `everything` grants all IP traffic to all destinations, and `scoped` uses that agent's `allow` entries.",
        "source_checked": true,
        "source_file": "README.md",
        "verdict": "yes"
      }
    ],
    "cycle_checks": [
      {
        "claim": "Scheduled or looping main behavior",
        "command": "",
        "evidence": "Inspected README.md and agent_access.py entry points: this is a finite offline CLI with summary, validate, diff, and generate commands; it has no scheduler, recurring loop, webhook, or cycle trigger.",
        "expected": "identify the product trigger",
        "input": "source inspection",
        "kind": "cycle",
        "outcome": "Inspected README.md and agent_access.py entry points: this is a finite offline CLI with summary, validate, diff, and generate commands; it has no scheduler, recurring loop, webhook, or cycle trigger.",
        "source": "repository entry points",
        "verdict": "yes"
      }
    ],
    "details": {
      "argv": [
        "python3",
        "agent_access.py",
        "summary"
      ],
      "kind": "cli",
      "needs_browser": false,
      "needs_credentials": false,
      "returncode": 0,
      "scope": "product operation",
      "stderr": "",
      "stdout": "Agent Tailscale grants\nThis is an offline grant summary, not a connectivity or isolation guarantee.\nEffective access depends on the complete tailnet policy, device tags, subnet routers, and the LAN.\nAllowed LAN addresses or ranges may include another agent's LAN interface; those interfaces are not excluded.\nA range grants the listed TCP/UDP flows to every address it covers; service labels do not restrict destinations.\nScoped mode does not model or test ICMP; the everything preset grants all IP traffic, including ICMP.\nThis fragment does not revoke credentials, host permissions, or access provided elsewhere.\n\nagent-a (tag:agent-agent-a)\n  Everything preset: grants all IP traffic to all destinations.\n\nagent-b (tag:agent-agent-b)\n[excerpt truncated]",
      "working": true
    },
    "evidence_strength": "readme_checked",
    "example_checks": [
      {
        "claim": "Validate the checked-in policy",
        "command": "python3 agent_access.py validate",
        "deferred": false,
        "evidence": "Policy is valid.",
        "expected": "Policy is valid.",
        "input": "policy.json",
        "kind": "example",
        "outcome": "command completed successfully",
        "returncode": 0,
        "source": "README.md / Quickstart",
        "verdict": "yes"
      },
      {
        "claim": "Generate a Tailscale policy fragment",
        "command": "python3 agent_access.py generate --output <guest-path>",
        "deferred": false,
        "evidence": "",
        "expected": "Generated fragment contains tagOwners and grants",
        "input": "checked-in policy.json",
        "kind": "example",
        "outcome": "command completed successfully with no output",
        "returncode": 0,
        "source": "README.md / Quickstart",
        "verdict": "yes"
      }
    ],
    "status": "PASS"
  },
  "diagnosis": null
}