auto-sync: tudo-para-ia-mais-humana 2026-05-04 13:58:55

src/mais_humana/institutional_decisions.py

@@ -48,6 +48,25 @@ class DevelopmentActionAssessment:
     human_explanation: str
 
 
+@dataclass(frozen=True)
+class HumanReadinessSignal:
+    decision_id: str
+    status: str
+    visible_to_profile: str
+    evidence_fields: tuple[str, ...]
+    missing_for_human_confidence: tuple[str, ...]
+    next_question: str
+
+
+@dataclass(frozen=True)
+class HumanPolicyPanel:
+    policy_version: str
+    ok: bool
+    generated_at: str
+    signals: tuple[HumanReadinessSignal, ...]
+    summary: dict[str, int]
+
+
 def _impact(profile_id: str, expectation: str, signal: str, risk: str, question: str) -> HumanImpact:
     return HumanImpact(
         profile_id=profile_id,
@@ -336,3 +355,83 @@ def classify_development_action_for_humans(action: str, environment: str = "deve
         required_controls=("truthState", "actorId", "auditId", "dryRunWhenApplicable"),
         human_explanation="Simulacao auditavel em desenvolvimento pode ser executada para avancar a rodada.",
     )
+
+
+def build_human_policy_readiness_panel(
+    available_evidence: dict[str, tuple[str, ...]] | None = None,
+) -> HumanPolicyPanel:
+    default_evidence_by_decision = {
+        "docs_full_operational_platform": ("documentId", "sourceHash", "authority", "truthState", "missingTopics"),
+        "mcp_required_cross_platform_acceptance": (
+            "originPlatformId",
+            "destinationPlatformId",
+            "contractHash",
+            "sourceRecordsHash",
+            "permissionId",
+            "evidenceId",
+            "traceId",
+            "auditId",
+        ),
+        "ten_year_institutional_retention": (
+            "retentionClass",
+            "retentionYears",
+            "legalHold",
+            "rollbackPlan",
+            "beforeAfterEvidence",
+        ),
+        "live_sensitive_data_purge_forbidden": (
+            "cleanupClassification",
+            "allowedTerms",
+            "forbiddenTerms",
+            "sensitiveDataCheck",
+        ),
+        "canonical_platform_names": ("canonicalName", "aliasStatus", "ownerPlatformId", "providerId"),
+        "development_execution_for_gpt_codex": ("truthState", "actorId", "auditId", "dryRun", "environment"),
+    }
+    evidence_by_decision = {
+        **default_evidence_by_decision,
+        **(available_evidence or {}),
+    }
+    signals: list[HumanReadinessSignal] = []
+    for decision in INSTITUTIONAL_DECISIONS:
+        evidence = tuple(evidence_by_decision.get(decision.decision_id, ()))
+        expected = set(decision.expected_mcp_evidence)
+        missing = tuple(sorted(expected.difference(evidence)))
+        status = "ready" if not missing else "partial" if evidence else "blocked"
+        profile = decision.affected_profiles[0]
+        signals.append(
+            HumanReadinessSignal(
+                decision_id=decision.decision_id,
+                status=status,
+                visible_to_profile=profile.profile_id,
+                evidence_fields=evidence,
+                missing_for_human_confidence=missing,
+                next_question=profile.next_human_question if missing else "A evidencia ja permite resposta humana equivalente?",
+            )
+        )
+    summary = {
+        "ready": sum(1 for signal in signals if signal.status == "ready"),
+        "partial": sum(1 for signal in signals if signal.status == "partial"),
+        "blocked": sum(1 for signal in signals if signal.status == "blocked"),
+        "total": len(signals),
+    }
+    return HumanPolicyPanel(
+        policy_version=POLICY_VERSION,
+        ok=summary["blocked"] == 0,
+        generated_at="2026-05-04T00:00:00.000Z",
+        signals=tuple(signals),
+        summary=summary,
+    )
+
+
+def export_human_policy_readiness_panel(
+    available_evidence: dict[str, tuple[str, ...]] | None = None,
+) -> dict[str, object]:
+    panel = build_human_policy_readiness_panel(available_evidence)
+    return {
+        "ok": panel.ok,
+        "policy_version": panel.policy_version,
+        "generated_at": panel.generated_at,
+        "summary": panel.summary,
+        "signals": [asdict(signal) for signal in panel.signals],
+    }

tests/test_institutional_decisions.py

@@ -5,7 +5,9 @@ import unittest
 from mais_humana.institutional_decisions import (
     PLATFORM_ALIASES,
     build_human_decision_matrix,
+    build_human_policy_readiness_panel,
     classify_development_action_for_humans,
+    export_human_policy_readiness_panel,
     list_institutional_decisions,
     summarize_decisions,
 )
@@ -66,6 +68,24 @@ class InstitutionalDecisionHumanTests(unittest.TestCase):
         self.assertFalse(secret.allowed)
         self.assertEqual(secret.decision, "blocked_secret_exposure")
 
+    def test_human_policy_readiness_panel_marks_missing_evidence_as_partial(self) -> None:
+        panel = build_human_policy_readiness_panel(
+            {
+                "docs_full_operational_platform": ("documentId", "sourceHash", "authority", "truthState", "missingTopics"),
+                "mcp_required_cross_platform_acceptance": ("originPlatformId", "contractHash"),
+            }
+        )
+        self.assertTrue(panel.ok)
+        self.assertEqual(panel.summary["total"], 6)
+        mcp_signal = [signal for signal in panel.signals if signal.decision_id == "mcp_required_cross_platform_acceptance"][0]
+        self.assertEqual(mcp_signal.status, "partial")
+        self.assertIn("destinationPlatformId", mcp_signal.missing_for_human_confidence)
+
+        exported = export_human_policy_readiness_panel()
+        self.assertTrue(exported["ok"])
+        self.assertEqual(exported["summary"]["ready"], 6)
+        self.assertEqual(len(exported["signals"]), 6)
+
 
 if __name__ == "__main__":
     unittest.main()