Sprint 63: Learned Adapter Hints (Non-Authoritative) — Steps 859-868

Implements the learned adapter hints layer with governance guardrails:
- HintFeatureExtractor: extract features from decision ledgers (step 859)
- HintModelInterface: pair-specific hint query interface (step 860)
- DeterministicFallback: safe fallback when hints unavailable (step 861)
- HintConfidencePacket: confidence bands and escalation logic (step 862)
- HintABHarness: A/B harness to measure hint effectiveness (step 863)
- HintRollbackControl: suppress and lift hint suppression per pair (step 864)
- whetstone_get_adapter_hints MCP tool (step 865)
- whetstone_set_hint_policy MCP tool (step 866)
- HintSafetyGuardrails: non-authoritative enforcement + audit (step 867)
- Sprint63IntegrationSummary (step 868)

All 10 steps passing (94 tests). Governance rule: learned hints may
suggest; deterministic policy decides.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

editor/tests/step863_test.cpp

@@ -0,0 +1,58 @@
+// Step 863: A/B harness for hint effectiveness (10 tests)
+#include "graduation/HintABHarness.h"
+#include <iostream>
+static int p=0,f=0;
+#define T(n) { std::cout << "  " << #n << "... "; }
+#define P() { std::cout << "PASS\n"; ++p; }
+#define F(m) { std::cout << "FAIL: " << m << "\n"; ++f; }
+#define C(c,m) if(!(c)){F(m);return;}
+
+void t1(){T(experiment_id_set);
+    ABVariant ctrl{"control",10,5}; ABVariant trt{"hint_guided",10,8};
+    auto r=HintABHarness::evaluate("exp-1",ctrl,trt);
+    C(r.experimentId=="exp-1","id");P();}
+void t2(){T(lift_positive_when_treatment_better);
+    ABVariant ctrl{"control",10,5}; ABVariant trt{"hint_guided",10,8};
+    auto r=HintABHarness::evaluate("exp-1",ctrl,trt);
+    C(r.lift>0.0f,"lift");P();}
+void t3(){T(treatment_wins_when_lift_gt_threshold);
+    ABVariant ctrl{"control",10,4}; ABVariant trt{"hint_guided",10,9};
+    auto r=HintABHarness::evaluate("exp-1",ctrl,trt);
+    C(r.treatmentWins,"wins");P();}
+void t4(){T(treatment_not_wins_small_lift);
+    ABVariant ctrl{"control",10,5}; ABVariant trt{"hint_guided",10,5};
+    auto r=HintABHarness::evaluate("exp-1",ctrl,trt);
+    C(!r.treatmentWins,"no win");P();}
+void t5(){T(zero_total_zero_rate);
+    ABVariant ctrl{"control",0,0}; ABVariant trt{"hint_guided",0,0};
+    auto r=HintABHarness::evaluate("exp-1",ctrl,trt);
+    C(r.lift==0.0f,"zero");P();}
+void t6(){T(control_stored);
+    ABVariant ctrl{"control",10,5}; ABVariant trt{"hint_guided",10,8};
+    auto r=HintABHarness::evaluate("exp-1",ctrl,trt);
+    C(r.control.variantId=="control","ctrl");P();}
+void t7(){T(treatment_stored);
+    ABVariant ctrl{"control",10,5}; ABVariant trt{"hint_guided",10,8};
+    auto r=HintABHarness::evaluate("exp-1",ctrl,trt);
+    C(r.treatment.variantId=="hint_guided","trt");P();}
+void t8(){T(negative_lift_treatment_loses);
+    ABVariant ctrl{"control",10,8}; ABVariant trt{"hint_guided",10,4};
+    auto r=HintABHarness::evaluate("exp-1",ctrl,trt);
+    C(!r.treatmentWins,"lose");P();}
+void t9(){T(to_json_has_lift);
+    ABVariant ctrl{"control",10,5}; ABVariant trt{"hint_guided",10,8};
+    auto r=HintABHarness::evaluate("exp-1",ctrl,trt);
+    auto j=HintABHarness::toJson(r);
+    C(j.contains("lift"),"lift");P();}
+void t10(){T(to_json_treatment_wins);
+    ABVariant ctrl{"control",10,4}; ABVariant trt{"hint_guided",10,9};
+    auto r=HintABHarness::evaluate("exp-1",ctrl,trt);
+    auto j=HintABHarness::toJson(r);
+    C(j.contains("treatment_wins"),"wins");P();}
+
+int main(){
+    std::cout<<"Step 863: A/B harness for hint effectiveness\n";
+    t1();t2();t3();t4();t5();t6();t7();t8();t9();t10();
+    std::cout<<"\nResults: "<<p<<"/"<<(p+f)<<" passed\n";
+    return f?1:0;
+}