feat: propagate execution evidence across iterations and enhance reports

- Carry execution evidence forward so reviewer/senior prompts in
  subsequent iterations can inspect prior transcript and command data
- Add {execution_evidence} to REVIEW_ONLY templates (en/ko)
- Add evidence summary table to iteration reports
- Fix test_agentic to match stdin-based prompt delivery for Claude
- Add expanded claim/no-change marker tests and cross-iteration
  evidence propagation tests

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

cross_eval/pipeline.py

@@ -338,6 +338,13 @@ def _run_simple_pipeline(
                     if tracker:
                         input_contents["previous_senior_tracker"] = tracker
 
+            # Carry execution evidence forward so subsequent iterations'
+            # reviewer/senior prompts can inspect prior transcript data.
+            if step_results:
+                input_contents["execution_evidence"] = _format_execution_evidence(
+                    step_results,
+                )
+
             iterations.append(iter_result)
 
             # ESCALATE check (highest priority)
@@ -531,6 +538,13 @@ def _run_phased_pipeline(
                         if tracker:
                             input_contents["previous_senior_tracker"] = tracker
 
+                # Carry execution evidence forward so subsequent iterations'
+                # reviewer/senior prompts can inspect prior transcript data.
+                if step_results:
+                    input_contents["execution_evidence"] = _format_execution_evidence(
+                        step_results,
+                    )
+
                 iterations.append(iter_result)
 
                 # ESCALATE check
@@ -1133,16 +1147,33 @@ def _build_context(
     max_iterations: int,
     step_results: dict[str, AgentResult] | None = None,
 ) -> dict[str, str]:
-    """Build the template context dict."""
+    """Build the template context dict.
+
+    Execution evidence from prior iterations is carried forward in
+    ``input_contents["execution_evidence"]``.  When the current iteration
+    has its own step results, the evidence is merged so reviewers/seniors
+    see both prior and current data.
+    """
     context: dict[str, str] = {}
     context.update(input_contents)
     context.update(step_outputs)
     context["feedback"] = feedback
     context["iteration"] = str(iteration)
     context["max_iterations"] = str(max_iterations)
-    # Surface execution evidence from prior steps so reviewers can inspect it
+    # Surface execution evidence from prior steps so reviewers can inspect it.
+    # Prior-iteration evidence may already live in context via input_contents.
+    prior_evidence = context.get("execution_evidence", "")
     if step_results:
-        context["execution_evidence"] = _format_execution_evidence(step_results)
+        current_evidence = _format_execution_evidence(step_results)
+        if prior_evidence and prior_evidence != "(no prior execution evidence)":
+            context["execution_evidence"] = (
+                "# Prior Iteration Evidence\n"
+                + prior_evidence
+                + "\n\n# Current Iteration Evidence\n"
+                + current_evidence
+            )
+        else:
+            context["execution_evidence"] = current_evidence
     return context
 
 
@@ -1164,6 +1195,7 @@ def _format_execution_evidence(
             f"- Command: `{result.command_preview}`" if result.command_preview else "",
             f"- Exit code: {result.exit_code}",
             f"- Duration: {result.duration_seconds}s",
+            f"- Output size: {len(result.output)} chars",
         ]
         section = [line for line in section if line]
         if result.transcript:

cross_eval/prompts.py

@@ -243,9 +243,14 @@ You are tasked with reviewing existing code against a plan and checklist.
 ## Previous Review (iteration {iteration} of {max_iterations})
 {feedback}
 
+## Execution Evidence
+{execution_evidence}
+
 ## Review Instructions
 Explore the project directory thoroughly to understand the full codebase, \
-then evaluate the EXISTING code against ONLY the plan and checklist above.
+then evaluate the EXISTING code against ONLY the plan and checklist above. \
+Use the execution evidence above to verify agent claims against actual \
+command outputs and exit codes.
 
 You are NOT generating or modifying code. You are auditing what already exists.
 
@@ -314,9 +319,13 @@ REVIEW_ONLY_TEMPLATE_KO = """\
 ## 이전 리뷰 결과 ({max_iterations}회 중 {iteration}번째)
 {feedback}
 
+## 실행 증거
+{execution_evidence}
+
 ## 검토 지침
 프로젝트 디렉토리를 직접 탐색하여 전체 코드베이스를 파악한 뒤, \
-위 기획서와 체크리스트 기준으로 **기존 코드**를 평가하세요.
+위 기획서와 체크리스트 기준으로 **기존 코드**를 평가하세요. \
+위 실행 증거를 활용하여 에이전트의 주장을 실제 명령어 출력과 종료 코드로 검증하세요.
 
 코드를 생성하거나 수정하지 마세요. 이미 존재하는 코드를 감사하는 것이 목적입니다.
 

cross_eval/report.py

@@ -58,6 +58,12 @@ _STRINGS: dict[str, dict[str, str]] = {
         "metrics_total_issues": "Total Issues",
         "metrics_na": "N/A",
         "iteration_details": "Iteration Details",
+        "evidence_summary": "Evidence Summary",
+        "evidence_agent": "Agent",
+        "evidence_exit_code": "Exit Code",
+        "evidence_duration": "Duration",
+        "evidence_output_size": "Output Size",
+        "evidence_transcript": "Execution transcript",
     },
     "ko": {
         "title": "교차 검증 리포트",
@@ -99,6 +105,12 @@ _STRINGS: dict[str, dict[str, str]] = {
         "metrics_total_issues": "총 이슈",
         "metrics_na": "해당 없음",
         "iteration_details": "반복 상세",
+        "evidence_summary": "실행 증거 요약",
+        "evidence_agent": "에이전트",
+        "evidence_exit_code": "종료 코드",
+        "evidence_duration": "소요 시간",
+        "evidence_output_size": "출력 크기",
+        "evidence_transcript": "실행 트랜스크립트",
     },
 }
 
@@ -377,6 +389,30 @@ def _append_iteration_steps(
     If *skip_extraction* is True, out-of-scope and review-metrics parsing
     is skipped (useful when a pre-scan already collected that data).
     """
+    # Evidence summary table — quick overview of all steps' execution data
+    has_evidence = any(
+        iter_result.step_results.get(s.output_key) for s in steps
+    )
+    if has_evidence:
+        s_step = _t(config, "step")
+        s_agent = _t(config, "evidence_agent")
+        s_exit = _t(config, "evidence_exit_code")
+        s_dur = _t(config, "evidence_duration")
+        s_size = _t(config, "evidence_output_size")
+        lines.append(f"**{_t(config, 'evidence_summary')}**\n")
+        lines.append(f"| {s_step} | {s_agent} | {s_exit} | {s_dur} | {s_size} |")
+        lines.append("|------|-------|-----------|----------|-------------|")
+        for step in steps:
+            ar = iter_result.step_results.get(step.output_key)
+            out = iter_result.step_outputs.get(step.output_key, "")
+            if ar:
+                lines.append(
+                    f"| {step.name} | {ar.agent_name} "
+                    f"| {ar.exit_code} | {ar.duration_seconds}s "
+                    f"| {len(out)} chars |"
+                )
+        lines.append("")
+
     for step in steps:
         agent_result = iter_result.step_results.get(step.output_key)
         output = iter_result.step_outputs.get(step.output_key, "")
@@ -410,8 +446,9 @@ def _append_iteration_steps(
             transcript_preview = agent_result.transcript[:1500]
             if len(agent_result.transcript) > 1500:
                 transcript_preview += "\n... (truncated)"
+            transcript_label = _t(config, "evidence_transcript")
             lines.append("<details>")
-            lines.append("<summary>Execution transcript</summary>\n")
+            lines.append(f"<summary>{transcript_label}</summary>\n")
             lines.append(transcript_preview)
             lines.append("\n</details>\n")